Publications

Self-Attention for Medical Imaging - On the need for evaluations beyond mere benchmarking
Tristan Piater and Niklas Penzel and Gideon Stein and Joachim Denzler.
Communications in Computer and Information Science. 2025. (in press)
[bibtex] [abstract]

Change Penalized Tuning to Reduce Pre-trained Biases
Niklas Penzel and Gideon Stein and Joachim Denzler.
Communications in Computer and Information Science. 2025. (in press)
[bibtex] [abstract]

Assessing 3D Volumetric Asymmetry in Facial Palsy Patients via Advanced Multi-view Landmarks and Radial Curves
Tim Büchner and Sven Sickert and Gerd F. Volk and Orlando Guntinas-Lichius and Joachim Denzler.
Machine Vision and Applications. 36 (1): 2025.
[bibtex] [abstract]

An Automatic, Objective Method to Measure and Visualize Volumetric Changes in Patients with Facial Palsy during 3D Video Recordings [Abstract]
Tim Büchner and Sven Sickert and Gerd F. Volk and Joachim Denzler and Orlando Guntinas-Lichius.
95th Annual Meeting German Society of Oto-Rhino-Laryngology, Head and Neck Surgery e. V., Bonn. 2024.
[bibtex] [web] [abstract]

Exploiting Text-Image Latent Spaces for the Description of Visual Concepts
Laines Schmalwasser and Jakob Gawlikowski and Joachim Denzler and Julia Niebling.
International Conference on Pattern Recognition (ICPR). 2024. (accepted)
[bibtex] [abstract]

When Medical Imaging Met Self-Attention: A Love Story That Didnt Quite Work Out
Tristan Piater and Niklas Penzel and Gideon Stein and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 149-158. 2024.
[bibtex] [web] [abstract]

Measuring and Visualizing Volumetric Changes Before and After 10-Day Biofeedback Therapy in Patients with Synkinetic Facial Palsy Using 3D Video Recordings [Abstract]
Tim Büchner and Sven Sickert and Gerd F. Volk and Martin Heinrich and Joachim Denzler and Orlando Guntinas-Lichius.
Congress of the Confederation of European ORL-HNS. 2024.
[bibtex] [pdf] [web] [abstract]

Facing Asymmetry - Uncovering the Causal Link between Facial Symmetry and Expression Classifiers using Synthetic Interventions
Tim Büchner and Niklas Penzel and Orlando Guntinas-Lichius and Joachim Denzler.
Asian Conference on Computer Vision (ACCV). 2024. (accepted at ACCV)
[bibtex] [pdf] [abstract]

Functional Tensor Decompositions for Physics-Informed Neural Networks
Sai Karthikeya Vemuri and Tim Büchner and Julia Niebling and Joachim Denzler.
International Conference on Pattern Recognition (ICPR). 2024. (accepted at ICPR)
[bibtex] [web] [abstract]

Determining the Community Composition of Herbaceous Species from Images using Convolutional Neural Networks
Matthias Körschens and Solveig Franziska Bucher and Paul Bodesheim and Josephine Ulrich and Joachim Denzler and Christine Römermann.
Ecological Informatics. 80: pages 102516. 2024.
[bibtex] [web] [abstract]

The Power of Properties: Uncovering the Influential Factors in Emotion Classification
Tim Büchner and Niklas Penzel and Orlando Guntinas-Lichius and Joachim Denzler.
International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI). 2024.
[bibtex] [web] [abstract]

How Interpretable Machine Learning Can Benefit Process Understanding in the Geosciences
Shijie Jiang and Lily-belle Sweet and Georgios Blougouras and Alexander Brenning and Wantong Li and Markus Reichstein and Joachim Denzler and Wei Shangguan and Guo Yu and Feini Huang and Jakob Zscheischler.
Earth's Future. 12 (7): pages e2024EF004540. 2024.
[bibtex] [web] [abstract]

Robust Skin Color Driven Privacy-Preserving Face Recognition via Function Secret Sharing
Dong Han and Yufan Jiang and Yong Li and Ricardo Mendes and Joachim Denzler.
International Conference on Image Processing (ICIP). 2024. (accepted)
[bibtex] [web] [abstract]

JeFaPaTo - A joint toolbox for blinking analysis and facial features extraction
Tim Büchner and Oliver Mothes and Orlando Guntinas-Lichius and Joachim Denzler.
Journal of Open Source Software. 9 (97): pages 6425. 2024.
[bibtex] [pdf] [web]

Physics Informed Modeling of Ecosystem Respiration via Dynamic Mode Decomposition with Control Input
Maha Shadaydeh and Joachim Denzler and Mirco Migliavacca.
ICLR Workshop on Machine Learning for Remote Sensing (ICLR-WS). 2024.
[bibtex] [web] [abstract]

Data-driven Prediction of Large Infrastructure Movements Through Persistent Scatterer Time Series Modeling
Gideon Stein and Jonas Ziemer and Carolin Wicker and Jannik Jaenichen and Gabriele Demisch and Daniel Kloepper and Katja Last and Joachim Denzler and Christiane Schmullius and Maha Shadaydeh and Cl{\'e}mence Dubois.
IEEE International Geoscience and Remote Sensing Symposium (IGARSS). pages 8669-8673. 2024.
[bibtex] [pdf] [abstract]

Embracing the Black Box: Heading Towards Foundation Models for Causal Discovery from Time Series Data
Gideon Stein and Maha Shadaydeh and Joachim Denzler.
AAAI Workshop on AI for Time-series (AAAI-WS). 2024.
[bibtex] [pdf] [web] [abstract]

Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-regenerative Life Support System Telemetry
Ferdinand Rewicki and Jakob Gawlikowski and Julia Niebling and Joachim Denzler.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). Pages 207-222. 2024.
[bibtex] [web] [abstract]

Privacy-Preserving Face Recognition in Hybrid Frequency-Color Domain
Dong Han and Yong Li and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 536-546. 2024.
[bibtex] [web] [abstract]

Deep-Learning Based Causal Inference: A Feasibility Study Based on Three Years of Tectonic-Climate Data From Moxa Geodynamic Observatory
Wasim Ahmad and Valentin Kasburg and Nina Kukowski and Maha Shadaydeh and Joachim Denzler.
Earth and Space Science. 11 (10): pages e2023EA003430. 2024.
[bibtex] [web] [abstract]

A Belowground Perspective on the Nexus Between Biodiversity Change, Climate Change, and Human Well-being
Nico Eisenhauer and Karin Frank and Alexandra Weigelt and Bartosz Bartkowski and R\'{e}my Beugnon and Katja Liebal and Miguel Mahecha and Martin Quaas and Djamil Al-Halbouni and Ana Bastos and Friedrich J. Bohn and Mariana Madruga de Brito and Joachim Denzler and Hannes Feilhauer and Rico Fischer and Immo Fritsche and Claudia Guimaraes-Steinicke and Martin H\"{a}nsel and Daniel B. M. Haun and Hartmut Herrmann and Andreas Huth and Heike Kalesse-Los and Michael Koetter and Nina Kolleck and Melanie Krause and Marlene Kretschmer and Pedro J. Leit{\~a}o and Torsten Masson and Karin Mora and Birgit M\"{u}ller and Jian Peng and Mira L. P\"{o}hlker and Leonie Ratzke and Markus Reichstein and Solveig Richter and Nadja R\"{u}ger and Beatriz S\'{a}nchez-Parra and Maha Shadaydeh and Sebastian Sippel and Ina Tegen and Daniela Thr\"{a}n and Josefine Umlauft and Manfred Wendisch and Kevin Wolf and Christian Wirth and Hannes Zacher and S\"{o}nke Zaehle and Johannes Quaas.
Journal of Sustainable Agriculture and Environment. 3 (2): pages e212108. 2024.
[bibtex] [web] [abstract]

Unsupervised Learning of Eye State Prototypes for Semantically Rich Blinking Detection
Yuxuan Xie and Tim Büchner and Lukas Schuhmann and Orlando Guntinas-Lichius and Joachim Denzler.
Digital Health & Informatics Innovations for Sustainable Health Care Systems. 2024.
[bibtex] [pdf] [web] [code]

Deep Learning-based Group Causal Inference in Multivariate Time-series
Wasim Ahmad and Maha Shadaydeh and Joachim Denzler.
AAAI Workshop on AI for Time-series (AAAI-WS). 2024.
[bibtex] [pdf] [web] [abstract]

Investigating the Effects of Plant Diversity on Soil Thermal Diffusivity Using Physics- Informed Neural Networks
Gideon Stein and Sai Karthikeya Vemuri and Yuanyuan Huang and Anne Ebeling and Nico Eisenhauer and Maha Shadaydeh and Joachim Denzler.
ICLR Workshop on AI4DifferentialEquations In Science (ICLR-WS). 2024.
[bibtex] [pdf] [web]

Regime Identification for Improving Causal Analysis in Non-stationary Timeseries
Wasim Ahmad and Maha Shadaydeh and Joachim Denzler.
arXiv preprint arXiv:2405.02315. 2024.
[bibtex] [pdf] [web] [abstract]

Few-Shot Learning with Novelty Detection
Kim Bjerge and Paul Bodesheim and Henrik Karstoft.
International Conference on Deep Learning Theory and Applications ({DeLTA}). 2024. Best Paper Award
[bibtex] [web] [abstract]

Automated Analysis of Spontaneous Eye Blinking in Patients with Acute Facial Palsy or Facial Synkinesis
Lukas Schuhmann and Tim Büchner and Martin Heinrich and Gerd Fabian Volk and Joachim Denzler and Orlando {Guntinas-Lichius.
. 14 (1): pages 17726. 2024.
[bibtex] [pdf] [web] [abstract]

Estimating Soil Hydraulic Parameters for Unsaturated Flow using Physics-Informed Neural Networks
Sai Karthikeya Vemuri and Tim Büchner and Joachim Denzler.
International Conference on Computational Science (ICCS). Pages 338-351. 2024.
[bibtex] [abstract]

Reducing the Gap Between Mimics and Muscles by Enabling Facial Feature Analysis during sEMG Recordings [Abstract]
Tim Büchner and Sven Sickert and Gerd F. Volk and Christoph Anders and Joachim Denzler and Orlando Guntinas-Lichius.
Congress of the Confederation of European ORL-HNS. 2024.
[bibtex] [pdf] [web] [abstract]

Reducing Bias in Pre-trained Models by Tuning while Penalizing Change
Niklas Penzel and Gideon Stein and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 90-101. 2024.
[bibtex] [web] [abstract]

Gaussian Latent Representations for Uncertainty Estimation using Mahalanobis Distance in Deep Classifiers
Aishwarya Venkataramanan and Assia Benbihi and Martin Laviale and C{\'e}dric Pradalier.
ICCV Workshop on Workshop on Uncertainty Quantification for Computer Vision (ICCV-WS). 2023.
[bibtex] [web] [abstract]

From Faces To Volumes - Measuring Volumetric Asymmetry in 3D Facial Palsy Scans
Tim Büchner and Sven Sickert and Gerd F. Volk and Orlando Guntinas-Lichius and Joachim Denzler.
International Symposium on Visual Computing (ISVC). Pages 121-132. 2023. Best Paper Award
[bibtex] [web] [abstract]

Unified Automatic Plant Cover and Phenology Prediction
Matthias Körschens and Solveig Franziska Bucher and Christine Römermann and Joachim Denzler.
ICCV Workshop on Computer Vision in Plant Phenotyping and Agriculture (CVPPA). 2023.
[bibtex] [pdf] [abstract]

Usefulness of Synthetic Datasets for Diatom Automatic Detection using a Deep-learning Approach
Aishwarya Venkataramanan and Pierre Faure-Giovagnoli and Cyril Regan and David Heudre and C{\'e}cile Figus and Philippe Usseglio-Polatera and C{\'e}dric Pradalier and Martin Laviale.
Engineering Applications of Artificial Intelligence. 117: pages 105594. 2023.
[bibtex] [web] [abstract]

Improving Data Efficiency for Plant Cover Prediction with Label Interpolation and Monte-Carlo Cropping
Matthias Körschens and Solveig Franziska Bucher and Christine Römermann and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). 2023.
[bibtex] [pdf] [web] [supplementary] [abstract]

Simplified Concrete Dropout - Improving the Generation of Attribution Masks for Fine-grained Classification
Dimitri Korsch and Maha Shadaydeh and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). 2023.
[bibtex] [pdf] [code] [supplementary] [abstract]

Beyond Debiasing: Actively Steering Feature Selection via Loss Regularization
Jan Blunk and Niklas Penzel and Paul Bodesheim and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). 2023.
[bibtex] [pdf] [abstract]

Integrating Visual and Semantic Similarity Using Hierarchies for Image Retrieval
Aishwarya Venkataramanan and Martin Laviale and C{\'e}dric Pradalier.
International Conference on Computer Vision Systems (ICVS). Pages 422431. 2023.
[bibtex] [web] [abstract]

Lets Get the FACS Straight - Reconstructing Obstructed Facial Features
Tim Büchner and Sven Sickert and Gerd F. Volk and Christoph Anders and Orlando Guntinas-Lichius and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 727-736. 2023.
[bibtex] [pdf] [web] [abstract]

Plant Diversity Stabilizes Soil Temperature
Yuanyuan Huang and Gideon Stein and Olaf Kolle and Karl Kuebler and Ernst-Detlef Schulze and Hui Dong and David Eichenberg and Gerd Gleixner and Anke Hildebrandt and Markus Lange and Christiane Roscher and Holger Schielzeth and Bernhard Schmid and Alexandra Weigelt and Wolfgang W. Weisser and Maha Shadaydeh and Joachim Denzler and Anne Ebeling and Nico Eisenhauer.
bioRxiv. pages 2023-03. 2023.
[bibtex] [pdf]

Enhanced Stability of Grassland Soil Temperature by Plant Diversity
Yuanyuan Huang and Gideon Stein and Olaf Kolle and Karl Kuebler and Ernst-Detlef Schulze and Hui Dong and David Eichenberg and Gerd Gleixner and Anke Hildebrandt and Markus Lange and Christiane Roscher and Holger Schielzeth and Bernhard Schmid and Alexandra Weigelt and Wolfgang W. Weisser and Maha Shadaydeh and Joachim Denzler and Anne Ebeling and Nico Eisenhauer.
Nature Geoscience. pages 1-7. 2023.
[bibtex] [abstract]

Is It Worth It? Comparing Six Deep and Classical Methods for Unsupervised Anomaly Detection in Time Series
Ferdinand Rewicki and Joachim Denzler and Julia Niebling.
Applied Sciences. 13 (3): 2023.
[bibtex] [web] [abstract]

Hard is the Task, the Samples are Few: A German Chiasmus Dataset
Felix Schneider and Sven Sickert and Phillip Brandes and Sophie Marshall and Joachim Denzler.
Language Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC). Pages 255-260. 2023.
[bibtex] [code] [abstract]

Gradient Statistics-Based Multi-Objective Optimization in Physics-Informed Neural Networks
Sai Karthikeya Vemuri and Joachim Denzler.
Sensors. 23 (21): 2023.
[bibtex] [pdf] [web] [abstract]

Abstract: Modeling and simulation of complex non-linear systems are essential in physics, engineering, and signal processing. Neural networks are widely regarded for such tasks due to their ability to learn complex representations from data. Training deep neural networks traditionally requires large amounts of data, which may not always be readily available for such systems. Contrarily, there is a large amount of domain knowledge in the form of mathematical models for the physics/behavior of such systems. A new class of neural networks called Physics-Informed Neural Networks (PINNs) has gained much attention recently as a paradigm for combining physics into neural networks. They have become a powerful tool for solving forward and inverse problems involving differential equations. A general framework of a PINN consists of a multi-layer perceptron that learns the solution of the partial differential equation (PDE) along with its boundary/initial conditions by minimizing a multi-objective loss function. This is formed by the sum of individual loss terms that penalize the output at different collocation points based on the differential equation and initial and boundary conditions. However, multiple loss terms arising from PDE residual and boundary conditions in PINNs pose a challenge in optimizing the overall loss function. This often leads to training failures and inaccurate results. We propose advanced gradient statistics-based weighting schemes for PINNs to address this challenge. These schemes utilize backpropagated gradient statistics of individual loss terms to appropriately scale and assign weights to each term, ensuring balanced training and meaningful solutions. In addition to the existing gradient statistics-based weighting schemes, we introduce kurtosis–standard deviation-based and combined mean and standard deviation-based schemes for approximating solutions of PDEs using PINNs. We provide a qualitative and quantitative comparison of these weighting schemes on 2D Poisson’s and Klein–Gordon’s equations, highlighting their effectiveness in improving PINN performance.

Der zeitliche Verlauf des emotionalen menschlichen Gesichtsausdruckes - die Entwicklung eines künstliche Intelligenz basierten Paradigmas zur Quantifizierung
Lena Mers and Oliver Mothes and Joachim Denzler and Orlando Guntinas-Lichius and Christian Dobel.
94. Jahresversammlung der Deutschen Gesellschaft für Hals-Nasen-Ohren-Heilkunde, Kopf- und Hals-Chirurgie e.V., Bonn. 2023.
[bibtex] [web] [abstract]

Analyzing the Behavior of Cauliflower Harvest-Readiness Models by Investigating Feature Relevances
Niklas Penzel and Jana Kierdorf and Ribana Roscher and Joachim Denzler.
ICCV Workshop on Computer Vision in Plant Phenotyping and Agriculture (CVPPA). Pages 572-581. 2023.
[bibtex] [pdf] [abstract]

Interpreting Art by Leveraging Pre-Trained Models
Niklas Penzel and Joachim Denzler.
International Conference on Machine Vision and Applications (MVA). Pages 1-6. 2023.
[bibtex] [abstract]

Improved Obstructed Facial Feature Reconstruction for Emotion Recognition with Minimal Change CycleGANs
Tim Büchner and Orlando Guntinas-Lichius and Joachim Denzler.
Advanced Concepts for Intelligent Vision Systems (Acivs). Pages 262-274. 2023. Best Paper Award
[bibtex] [web] [abstract]

Physics Informed Neural Networks for Aeroacoustic Source Estimation
Sai Karthikeya Vemuri and Joachim Denzler.
IACM Mechanistic Machine Learning and Digital Engineering for Computational Science Engineering and Technology. 2023.
[bibtex] [web] [abstract]

Abstract: Computational Aeroacoustics (CAA) is a critical domain within computational fluid dynamics (CFD) that focuses on understanding and predicting sound generation in aerodynamic systems. Accurate estimation of Lighthill sources, which play a pivotal role in deciphering acoustic phenomena, remains a challenging task, especially when confronted with noisy and missing flow data. This study explores the potential of Physics Informed Neural Networks (PINNs) to address these challenges and capture the complex flow dynamics inherent in CAA. The integration of PINNs in CFD has gained significant attention in recent years. PINNs blend deep learning techniques with fundamental physical principles, enabling accurate predictions and enhanced modeling capabilities. Their versatility has been demonstrated across various CFD applications, ranging from turbulence modeling to flow control optimization and mesh generation. However, their potential in the field of CAA, specifically in estimating Lighthill sources from flow data, remains largely unexplored. To investigate the effectiveness of PINNs in the context of CAA, we conduct a series of experiments using high-fidelity flow data obtained from common flow configurations, such as flow around a cylinder. Leveraging this data, we create three distinct datasets that represent different data imperfections. The first dataset involves the deliberate removal of certain data points, the second dataset incorporates the addition of random noise, and the third dataset combines both missing data and noise. By incorporating the governing Navier-Stokes equations, we train the PINNs using these three datasets. The PINNs, with their inherent capability to capture complex flow patterns, are employed to estimate the aeroacoustic source map. The predicted map obtained from the PINNs is then rigorously compared to the ground truth source map derived from the high-fidelity data. Through these experiments, we demonstrate the remarkable ability of PINNs to effectively estimate the aeroacoustic source map in the presence of noisy and missing data. This validation establishes the potential of PINNs as a powerful tool for aeroacoustic analysis and source characterization. The successful application of PINNs in this study opens up new ways for further advancements in aeroacoustics. By leveraging PINNs we can enhance noise reduction techniques, optimize design processes, and improve the overall efficiency of aerodynamic systems. In conclusion, this research showcases the potential of Physics Informed Neural Networks for accurate aeroacoustic source estimation in scenarios where data quality is compromised. These findings contribute to the growing body of knowledge in aeroacoustics and offer a pathway toward more robust and efficient analysis techniques in the field.

Using 2D and 3D Face Representations to Generate Comprehensive Facial Electromyography Intensity Maps
Tim Büchner and Sven Sickert and Roland Graßme and Christoph Anders and Orlando Guntinas-Lichius and Joachim Denzler.
International Symposium on Visual Computing (ISVC). Pages 136-147. 2023.
[bibtex] [web] [code] [abstract]

Predicting spatiotemporal variability in radial tree growth at the continental scale with machine learning
Paul Bodesheim and Flurin Babst and David C. Frank and Claudia Hartl and Christian S. Zang and Martin Jung and Markus Reichstein and Miguel D. Mahecha.
Environmental Data Science. 1: pages E9. 2022.
[bibtex] [abstract]

ZeTT-RADAR-Sonderver\"{o}ffentlichung - Hotspots und weie Flecken K\"{u}nstlicher Intelligenz
Thomas Engel and N\'{o}ra Fülöp and Oliver Mothes and Christian Schädlich.
ZeTT-RADAR-Sonderver\"{o}ffentlichung. 2022.
[bibtex] [pdf] [web]

Time Series Causal Link Estimation under Hidden Confounding using Knockoff Interventions
Violeta Teodora Trifunov and Maha Shadaydeh and Joachim Denzler.
NeurIPS Workshop on A Causal View on Dynamical Systems (NeurIPS-WS). 2022.
[bibtex] [pdf] [web] [abstract]

Metaphor Detection for Low Resource Languages: From Zero-Shot to Few-Shot Learning in Middle High German
Felix Schneider and Sven Sickert and Phillip Brandes and Sophie Marshall and Joachim Denzler.
LREC Workshop on Multiword Expression (LREC-WS). Pages 75-80. 2022.
[bibtex] [web] [code] [abstract]

A spatiotemporal stochastic climate model for benchmarking causal discovery methods for teleconnections
Xavier-Andoni Tibau and Christian Reimers and Andreas Gerhardus and Joachim Denzler and Veronika Eyring and Jakob Runge.
Environmental Data Science. 1: pages E12. 2022.
[bibtex] [web] [abstract]

Causal Discovery using Model Invariance through Knockoff Interventions
Wasim Ahmad and Maha Shadaydeh and Joachim Denzler.
ICML Workshop on Spurious Correlations, Invariance and Stability (ICML-WS). 2022.
[bibtex] [pdf] [web] [abstract]

Image Classification with Small Datasets: Overview and Benchmark
Lorenzo Brigato and Björn Barz and Luca Iocchi and Joachim Denzler.
IEEE Access. 10: pages 49233-49250. 2022.
[bibtex] [pdf] [web] [abstract]

Sequential Causal Effect Variational Autoencoder: Time Series Causal Link Estimation under Hidden Confounding
Violeta Teodora Trifunov and Maha Shadaydeh and Joachim Denzler.
arXiv preprint arXiv:2209.11497. 2022.
[bibtex] [web] [abstract]

Limb, Joint and Pelvic Kinematic Control in the Quail Coping with Steps Upwards and Downwards
Emanuel Andrada and Oliver Mothes and Heiko Stark and Matthew C. Tresch and Joachim Denzler and Martin S. Fischer and Reinhard Blickhan.
Scientific Reports. 12 (1): pages 15901. 2022.
[bibtex] [pdf] [web] [abstract]

A Method for Pipeline Leak Detection Based on Acoustic Imaging and Deep Learning
Sajjad Ahmad and Zahoor Ahmad and Cheol-Hong Kim and Jong-Myon Kim.
Sensors. 22 (4): pages 1562. 2022.
[bibtex] [abstract]

A Centrifugal Pump Fault Diagnosis Framework Based on Supervised Contrastive Learning
Sajjad Ahmad and Zahoor Ahmad and Jong-Myon Kim.
Sensors. 22 (17): pages 6448. 2022.
[bibtex] [abstract]

Towards a multisensor station for automated biodiversity monitoring
J. Wolfgang Wägele and Paul Bodesheim and Sarah J. Bourlat and Joachim Denzler and Michael Diepenbroek and Vera Fonseca and Karl-Heinz Frommolt and Matthias F. Geiger and Birgit Gemeinholzer and Frank Oliver Glöckner and Timm Haucke and Ameli Kirse and Alexander Kölpin and Ivaylo Kostadinov and Hjalmar S. Kühl and Frank Kurth and Mario Lasseck and Sascha Liedke and Florian Losch and Sandra Müller and Natalia Petrovskaya and Krzysztof Piotrowski and Bernd Radig and Christoph Scherber and Lukas Schoppmann and Jan Schulz and Volker Steinhage and Georg F. Tschan and Wolfgang Vautz and Domenico Velotto and Maximilian Weigend and Stefan Wildermann.
Basic and Applied Ecology. 59: pages 105-138. 2022.
[bibtex] [web] [abstract]

Abstract: Rapid changes of the biosphere observed in recent years are caused by both small and large scale drivers, like shifts in temperature, transformations in land-use, or changes in the energy budget of systems. While the latter processes are easily quantifiable, documentation of the loss of biodiversity and community structure is more difficult. Changes in organismal abundance and diversity are barely documented. Censuses of species are usually fragmentary and inferred by often spatially, temporally and ecologically unsatisfactory simple species lists for individual study sites. Thus, detrimental global processes and their drivers often remain unrevealed. A major impediment to monitoring species diversity is the lack of human taxonomic expertise that is implicitly required for large-scale and fine-grained assessments. Another is the large amount of personnel and associated costs needed to cover large scales, or the inaccessibility of remote but nonetheless affected areas. To overcome these limitations we propose a network of Automated Multisensor stations for Monitoring of species Diversity (AMMODs) to pave the way for a new generation of biodiversity assessment centers. This network combines cutting-edge technologies with biodiversity informatics and expert systems that conserve expert knowledge. Each AMMOD station combines autonomous samplers for insects, pollen and spores, audio recorders for vocalizing animals, sensors for volatile organic compounds emitted by plants (pVOCs) and camera traps for mammals and small invertebrates. AMMODs are largely self-containing and have the ability to pre-process data (e.g. for noise filtering) prior to transmission to receiver stations for storage, integration and analyses. Installation on sites that are difficult to access require a sophisticated and challenging system design with optimum balance between power requirements, bandwidth for data transmission, required service, and operation under all environmental conditions for years. An important prerequisite for automated species identification are databases of DNA barcodes, animal sounds, for pVOCs, and images used as training data for automated species identification. AMMOD stations thus become a key component to advance the field of biodiversity monitoring for research and policy by delivering biodiversity data at an unprecedented spatial and temporal resolution.

Weakly-Supervised Localization of Multiple Objects in Images using Cosine Loss
Björn Barz and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 287-296. 2022.
[bibtex] [abstract]

Automatic Objective Severity Grading of Peripheral Facial Palsy Using 3D Radial Curves Extracted from Point Clouds
Tim Büchner and Sven Sickert and Gerd F. Volk and Orlando Guntinas-Lichius and Joachim Denzler.
Challenges of Trustable AI and Added-Value on Health. 2022.
[bibtex] [web] [code] [abstract]

Pre-trained models are not enough: active and lifelong learning is important for long-term visual monitoring of mammals in biodiversity research. Individual identification and attribute prediction with image features from deep neural networks and decoupled decision models applied to elephants and great apes
Paul Bodesheim and Jan Blunk and Matthias Körschens and Clemens-Alexander Brust and Christoph Käding and Joachim Denzler.
Mammalian Biology. 102: pages 875-897. 2022.
[bibtex] [web] [abstract]

Abstract: Animal re-identification based on image data, either recorded manually by photographers or automatically with camera traps, is an important task for ecological studies about biodiversity and conservation that can be highly automatized with algorithms from computer vision and machine learning. However, fixed identification models only trained with standard datasets before their application will quickly reach their limits, especially for long-term monitoring with changing environmental conditions, varying visual appearances of individuals over time that differ a lot from those in the training data, and new occurring individuals that have not been observed before. Hence, we believe that active learning with human-in-the-loop and continuous lifelong learning is important to tackle these challenges and to obtain high-performance recognition systems when dealing with huge amounts of additional data that become available during the application. Our general approach with image features from deep neural networks and decoupled decision models can be applied to many different mammalian species and is perfectly suited for continuous improvements of the recognition systems via lifelong learning. In our identification experiments, we consider four different taxa, namely two elephant species: African forest elephants and Asian elephants, as well as two species of great apes: gorillas and chimpanzees. Going beyond classical re-identification, our decoupled approach can also be used for predicting attributes of individuals such as gender or age using classification or regression methods. Although applicable for small datasets of individuals as well, we argue that even better recognition performance will be achieved by improving decision models gradually via lifelong learning to exploit huge datasets and continuous recordings from long-term applications. We highlight that algorithms for deploying lifelong learning in real observational studies exist and are ready for use. Hence, lifelong learning might become a valuable concept that supports practitioners when analyzing large-scale image data during long-term monitoring of mammals.

Outcome Prediction and Murmur Detection in Sets of Phonocardiograms by a Deep Learning-Based Ensemble Approach
Sven Festag and Gideon Stein and Tim Büchner and Maha Shadaydeh and Joachim Denzler and Cord Spreckelsen.
Computing in Cardiology (CinC). Pages 1-4. 2022.
[bibtex] [pdf] [abstract]

Emerging technologies revolutionise insect ecology and monitoring
Roel van Klink and Tom August and Yves Bas and Paul Bodesheim and Aletta Bonn and Frode Fossoy and Toke T. Hoye and Eelke Jongejans and Myles H.M. Menz and Andreia Miraldo and Tomas Roslin and Helen E. Roy and Ireneusz Ruczynski and Dmitry Schigel and Livia Schäffler and Julie K. Sheard and Cecilie Svenningsen and Georg F. Tschan and Jana Wäldchen and Vera M.A. Zizka and Jens Aström and Diana E. Bowler.
Trends in Ecology \& Evolution. 37 (10): pages 872-885. 2022.
[bibtex] [abstract]

KI4KI: Neues Projekt zur regelmässigen {\"U}berwachung von Stauanlagen aus dem All
Clemence Dubois and Jannik Jänichen and Maha Shadaydeh and Gideon Stein and Alexandra Katz and Daniel Klöpper and Joachim Denzler and Christiane Schmullius and Katja Last.
Messtechnische {\"U}berwachung von Stauanlagen ; XII.Mittweidaer Talsperrentag. Pages 15-19. 2022.
[bibtex] [web] [abstract]

Partitioning of Net Ecosystem Exchange Using Dynamic Mode Decomposition and Time Delay Embedding
Maha Shadaydeh and Joachim Denzler and Mirco Migliavacca.
Engineering Proceedings. 18 (1): 2022.
[bibtex] [web] [abstract]

Optical Quantification of Surface Electrical Stimulation to Prevent Denervation Muscle Atrophy in 15 Patients with Facial Paralysis [Abstract]
Johannes Krauß and Gabriel Meincke and Maren Geitner and Dirk Arnold and Anna-Maria Kuttenreich and Valeria Mastryukova and Jan Beckmann and Wengelawit Misikire and Tim Büchner and Joachim Denzler and Orlando {Guntinas-Lichius} and Gerd F. Volk.
Abstracts of the 2022 Joint Annual Conference of the Austrian ({\"O}GBMT), German (VDE DGBMT) and Swiss (SSBE) Societies for Biomedical Engineering, including the 14th Vienna International Workshop on Functional Electrical Stimulation. 67: pages 541. 2022.
[bibtex] [abstract]

Abstract: Few studies showing therapeutic potentials of electrical stimulation (ES) of the facial surface in patients with facial palsy have been published so far. Not only muscular atrophy of the facial muscles but facial disfigurement represents the main issue for patient well-being. Therefore, objective methods are required to detect ES effects on facial symmetry within patients with complete unilateral facial paralysis. Methods Only patients with one-sided peripheral complete facial paralysis confirmed by needle-EMG were included and underwent ES twice a day for 20 min until the event of reinnervation or for a maximum of 1 year. ES-parameters were set during the first visit and confirmed/adapted every month thereafter. At each visit, patients underwent needle-electromyography, 2D-fotographic documentation and 3D-videos. Whereas 2D-images allow Euclidean measurements of facial symmetry, 3D-images permit detection of metrical divergence within both sides of face. Using the 2D and 3D-fotographic documentation, we aim to prove that ES is able to prevent muscular atrophy in patients with facial paralysis. Results In total 15 patients were recruited (medium 53 years, min. 25, max. 78; 8 female, 7 male). They underwent ES for a maximum of one year without serious adverse events. All patients were able to follow the ES protocol. On a short term, we could detect positive effects of ES on the extent of asymmetry of mouth corners. Preliminary results show positive effects leading to improvement of symmetry of denervated faces. Conclusion A positive short-term effect of ES on facial symmetry in patients with total paralysis could be shown. The improvement of optical appearance during ES has a positive effect on patients' satisfaction and resembles a promising, easily accessible marker for facial muscles in facial paralysis patients. Improving facial symmetry by ES might also be linked to preventing facial muscle atrophy. Acknowledgements Sponsored by DFG GU-463/12-1 and IZKF

A Comparison of Machine Learning Algorithms and Feature Sets for Automatic Vocal Emotion Recognition in Speech
Cem Dovgdu and Thomas Kessler and Dana Schneider and Maha Shadaydeh and Stefan R. Schweinberger.
Sensors. 22 (19): 2022.
[bibtex] [web] [abstract]

Beyond Global Average Pooling: Alternative Feature Aggregations for Weakly Supervised Localization
Matthias Körschens and Paul Bodesheim and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 180-191. 2022.
[bibtex] [pdf] [abstract]

A Data Driven Approach to Generate Realistic 3D Tree Barks
Aishwarya Venkataramanan and Antoine Richard and C{\'e}dric Pradalier.
Graphical Models. 123: pages 101166. 2022.
[bibtex] [web] [abstract]

Surface Electrostimulation Prevents Denervated Muscle Atrophy in Facial Paralysis: Ultrasound Quantification [Abstract]
Gabriel Meincke and Johannes Krauß and Maren Geitner and Dirk Arnold and Anna-Maria Kuttenreich and Valeria Mastryukova and Jan Beckmann and Wengelawit Misikire and Tim Büchner and Joachim Denzler and Orlando {Guntinas-Lichius} and Gerd F. Volk.
Abstracts of the 2022 Joint Annual Conference of the Austrian ({\"O}GBMT), German (VDE DGBMT) and Swiss (SSBE) Societies for Biomedical Engineering, including the 14th Vienna International Workshop on Functional Electrical Stimulation. 67: pages 542. 2022.
[bibtex] [abstract]

Abstract: Sparse evidence of the potentialities of surface stimulation (ES) for preventing muscle atrophy in patients with acute or chronic facial palsy have been published so far. Especially studies addressing objective imaging methods for paralysis quantification are currently required. Facial muscles as principal target of ES can be directly quantified via ultrasound, a swiftly feasible imaging method. Our study represents one of the few systematic evaluations of this approach within patients with complete unilateral facial paralysis. Methods A well-established ultrasound protocol for the quantification of area and grey levels was used to evaluate therapeutical effects on patients with facial paralysis using ES. Only patients with complete facial paralysis confirmed by needleelectromyography were included. Individual ES parameters were set during the first visit and confirmed/adapted every month thereafter. At each visit patients additionally underwent facial needle-electromyography to rule out reinnervation as well as ultrasound imaging of 7 facial and 2 chewing muscles. Results In total 15 patients were recruited (medium 53 years, min. 25, max. 78; 8 female, 7 male). They underwent ES for a maximum of 1 year without serious adverse events. All patients were able to follow the ES protocol. First results in the assessment of ultrasound imaging already indicate that electrically stimulated paralytic muscles do not experience any further cross-sectional area decrease in comparison to the contralateral side. Non-stimulated muscles do not provide significant changes. Similar effects on grey levels currently remain to be assessed to draw further conclusions. Conclusion ES is supposed to decelerate the process of atrophy of facial muscles in patients with complete facial paralysis. Thus, the muscular cross-sectional area does not seem to aggravate during the period of electrostimulation within sonographic assessment. This demonstrates the benefit of ES regarding the facial muscle atrophy in patients with complete facial paralysis.

Towards a Unified Benchmark for Monocular Radial Distortion Correction and the Importance of Testing on Real World Data
Christoph Theiß and Joachim Denzler.
International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI). Pages 59-71. 2022.
[bibtex] [web] [abstract]

Multistage Centrifugal Pump Fault Diagnosis Using Informative Ratio Principal Component Analysis
Zahoor Ahmad and Tuan-Khai Nguyen and Sajjad Ahmad and Cong Dai Nguyen and Jong-Myon Kim.
Sensors. 22 (1): pages 179. 2022.
[bibtex] [abstract]

Automated Visual Monitoring of Nocturnal Insects with Light-based Camera Traps
Dimitri Korsch and Paul Bodesheim and Gunnar Brehm and Joachim Denzler.
CVPR Workshop on Fine-grained Visual Classification (CVPR-WS). 2022.
[bibtex] [pdf] [web] [code] [abstract]

Investigating Neural Network Training on a Feature Level using Conditional Independence
Niklas Penzel and Christian Reimers and Paul Bodesheim and Joachim Denzler.
ECCV Workshop on Causality in Vision (ECCV-WS). Pages 383-399. 2022.
[bibtex] [pdf] [abstract]

Occlusion-Robustness of Convolutional Neural Networks via Inverted Cutout
Matthias Körschens and Paul Bodesheim and Joachim Denzler.
International Conference on Pattern Recognition (ICPR). Pages 2829-2835. 2022.
[bibtex] [pdf] [supplementary] [abstract]

Anomaly Attribution of Multivariate Time Series using Counterfactual Reasoning
Violeta Teodora Trifunov and Maha Shadaydeh and Björn Barz and Joachim Denzler.
IEEE International Conference on Machine Learning and Applications (ICMLA). Pages 166-172. 2021.
[bibtex] [pdf] [web] [abstract]

Automatic Plant Cover Estimation with Convolutional Neural Networks
Matthias Körschens and Paul Bodesheim and Christine Römermann and Solveig Franziska Bucher and Mirco Migliavacca and Josephine Ulrich and Joachim Denzler.
Computer Science for Biodiversity Workshop (CS4Biodiversity), INFORMATIK 2021. Pages 499-516. 2021.
[bibtex] [pdf] [abstract]

Analyzing the Direction of Emotional Influence in Nonverbal Dyadic Communication: A Facial-Expression Study
Maha Shadaydeh and Lea Müller and Dana Schneider and Martin Thümmel and Thomas Kessler and Joachim Denzler.
IEEE Access. 9: pages 73780-73790. 2021.
[bibtex] [pdf] [web] [presentation] [abstract]

Self-Supervised Learning from Semantically Imprecise Data
Clemens-Alexander Brust and Björn Barz and Joachim Denzler.
arXiv preprint arXiv:2104.10901. 2021.
[bibtex] [pdf] [abstract]

Finding Relevant Flood Images on Twitter using Content-based Filters
Björn Barz and Kai Schröter and Ann-Christin Kra and Joachim Denzler.
ICPR Workshop on Machine Learning Advances Environmental Science (MAES). Pages 5-14. 2021.
[bibtex] [pdf] [web] [abstract]

Content-based Image Retrieval and the Semantic Gap in the Deep Learning Era
Björn Barz and Joachim Denzler.
ICPR Workshop on Content-Based Image Retrieval (CBIR2020). Pages 245-260. 2021.
[bibtex] [pdf] [abstract]

End-to-end Learning of Fisher Vector Encodings for Part Features in Fine-grained Recognition
Dimitri Korsch and Paul Bodesheim and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 142-158. 2021.
[bibtex] [pdf] [web] [code] [abstract]

Conditional Adversarial Debiasing: Towards Learning Unbiased Classifiers from Biased Data
Christian Reimers and Paul Bodesheim and Jakob Runge and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 48-62. 2021.
[bibtex] [pdf] [abstract]

Conditional Dependence Tests Reveal the Usage of ABCD Rule Features and Bias Variables in Automatic Skin Lesion Classification
Christian Reimers and Niklas Penzel and Paul Bodesheim and Jakob Runge and Joachim Denzler.
CVPR ISIC Skin Image Analysis Workshop (CVPR-WS). Pages 1810-1819. 2021.
[bibtex] [pdf] [web] [abstract]

A Data-Driven Approach to Partitioning Net Ecosystem Exchange Using a Deep State Space Model
Violeta Teodora Trifunov and Maha Shadaydeh and Jakob Runge and Markus Reichstein and Joachim Denzler.
IEEE Access. 9: pages 107873-107883. 2021.
[bibtex] [web] [abstract]

Causal Inference in Non-linear Time-series using Deep Networks and Knockoff Counterfactuals
Wasim Ahmad and Maha Shadaydeh and Joachim Denzler.
IEEE International Conference on Machine Learning and Applications (ICMLA). Pages 449-454. 2021.
[bibtex] [pdf] [web] [abstract]

Data-Driven Detection of General Chiasmi Using Lexical and Semantic Features
Felix Schneider and Phillip Brandes and Björn Barz and Sophie Marshall and Joachim Denzler.
SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. Pages 96-100. 2021.
[bibtex] [web] [abstract]

Weakly Supervised Segmentation Pretraining for Plant Cover Prediction
Matthias Körschens and Paul Bodesheim and Christine Römermann and Solveig Franziska Bucher and Mirco Migliavacca and Josephine Ulrich and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 589-603. 2021.
[bibtex] [pdf] [supplementary] [abstract]

Carpe Diem: A Lifelong Learning Tool for Automated Wildlife Surveillance
Clemens-Alexander Brust and Björn Barz and Joachim Denzler.
Computer Science for Biodiversity Workshop (CS4Biodiversity), INFORMATIK 2021. Pages 417-423. 2021.
[bibtex] [pdf]

Lightweight Filtering of Noisy Web Data: Augmenting Fine-grained Datasets with Selected Internet Images
Julia Böhlke and Dimitri Korsch and Paul Bodesheim and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 466-477. 2021.
[bibtex] [pdf] [web] [abstract]

Tackling Inter-Class Similarity and Intra-Class Variance for Microscopic Image-based Classification
Aishwarya Venkataramanan and Martin Laviale and C{\'e}cile Figus and Philippe Usseglio-Polatera and C{\'e}dric Pradalier.
International Conference on Computer Vision Systems (ICVS). Pages 93103. 2021.
[bibtex] [web] [abstract]

Minimizing the Annotation Effort for Detecting Wildlife in Camera Trap Images with Active Learning
Daphne Auer and Paul Bodesheim and Christian Fiderer and Marco Heurich and Joachim Denzler.
Computer Science for Biodiversity Workshop (CS4Biodiversity), INFORMATIK 2021. Pages 547-564. 2021.
[bibtex] [pdf] [abstract]

Tune It or Don't Use It: Benchmarking Data-Efficient Image Classification
Lorenzo Brigato and Björn Barz and Luca Iocchi and Joachim Denzler.
ICCV Workshop on Visual Inductive Priors for Data-Efficient Deep Learning. 2021.
[bibtex] [pdf] [abstract]

Domain Adaptation and Active Learning for Fine-Grained Recognition in the Field of Biodiversity
Bernd Gruner and Matthias Körschens and Björn Barz and Joachim Denzler.
Findings of the CVPR Workshop on Continual Learning in Computer Vision (CLVision). 2021.
[bibtex] [abstract]

Automated Visual Large Scale Monitoring of Faunal Biodiversity
Bernd Radig and Paul Bodesheim and Dimitri Korsch and Joachim Denzler and Timm Haucke and Morris Klasen and Volker Steinhage.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 31 (3): pages 477-488. 2021.
[bibtex] [pdf] [web] [abstract]

Abstract: To observe biodiversity, the variety of plant and animal life in the world or in a particular habitat, human observers make the most common examinations, often assisted by technical equipment. Measuring objectively the number of different species of animals, plants, fungi, and microbes that make up the ecosystem can be difficult. In order to monitor changes in biodiversity, data have to be compared across space and time. Cameras are an essential sensor to determine the species range, abundance, and behavior of animals. The millions of recordings from camera traps set up in natural environments can no longer be analyzed by biologists. We started research on doing this analysis automatically without human interaction. The focus of our present sensor is on image capture of wildlife and moths. Special hardware elements for the detection of different species are designed, implemented, tested, and improved, as well as the algorithms for classification and counting of samples from images and image sequences, e.g., to calculate presence, absence, and abundance values or the duration of characteristic activities related to the spatial mobilities. For this purpose, we are developing stereo camera traps that allow spatial reconstruction of the observed animals. This allows three-dimensional coordinates to be recorded and the shape to be characterized. With this additional feature data, species identification and movement detection are facilitated. To classify and count moths, they are attracted to an illuminated screen, which is then photographed at intervals by a high-resolution color camera. To greatly reduce the volume of data, redundant elements and elements that are consistent from image to image are eliminated. All design decisions take into account that at remote sites and in fully autonomous operation, power supply on the one hand and possibilities for data exchange with central servers on the other hand are limited. Installation at hard-to-reach locations requires a sophisticated and demanding system design with an optimal balance between power requirements, bandwidth for data transmission, required service and operation in all environmental conditions for at least ten years.

Facial Behavior Analysis using 4D Curvature Statistics for Presentation Attack Detection
Martin Thümmel and Sven Sickert and Joachim Denzler.
IEEE International Workshop on Biometrics and Forensics (IWBF). Pages 1-6. 2021.
[bibtex] [web] [code] [abstract]

WikiChurches: A Fine-Grained Dataset of Architectural Styles with Real-World Challenges
Björn Barz and Joachim Denzler.
NeurIPS 2021 Track on Datasets and Benchmarks. 2021.
[bibtex] [pdf] [presentation] [abstract]

Exploiting Web Images for Moth Species Classification
Julia Böhlke and Dimitri Korsch and Paul Bodesheim and Joachim Denzler.
Computer Science for Biodiversity Workshop (CS4Biodiversity), INFORMATIK 2021. Pages 481-498. 2021.
[bibtex] [pdf] [web] [abstract]

Investigating the Consistency of Uncertainty Sampling in Deep Active Learning
Niklas Penzel and Christian Reimers and Clemens-Alexander Brust and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 159-173. 2021.
[bibtex] [pdf] [web] [abstract]

Counterfactual Generation with Knockoffs
Oana-Iuliana Popescu and Maha Shadaydeh and Joachim Denzler.
arXiv preprint arXiv:2102.00951. 2021.
[bibtex] [pdf] [web] [abstract]

Uncovering Stability Princicples of Avian Bipedal Uneven Locomotion
Emanuel Andrada and Oliver Mothes and Dirk Arnold and Joachim Denzler and Martin S. Fischer and Reinhard Blickhan.
26th Congress of the European Society of Biomechanics (ESB). 2021.
[bibtex]

Detecting Scenes in Fiction Using the Embedding Delta Signal
Felix Schneider and Björn Barz and Joachim Denzler.
KONVENS Shared Task on Scene Segmentation. 2021.
[bibtex]

Deep Learning Pipeline for Automated Visual Moth Monitoring: Insect Localization and Species Classification
Dimitri Korsch and Paul Bodesheim and Joachim Denzler.
INFORMATIK 2021, Computer Science for Biodiversity Workshop (CS4Biodiversity). Pages 443-460. 2021.
[bibtex] [pdf] [web] [code] [abstract]

Making Every Label Count: Handling Semantic Imprecision by Integrating Domain Knowledge
Clemens-Alexander Brust and Björn Barz and Joachim Denzler.
International Conference on Pattern Recognition (ICPR). 2020.
[bibtex] [pdf] [abstract]

Deep Learning--an Opportunity and a Challenge for Geo-and Astrophysics
Christian Reimers and Christian Requena-Mesa. 2020.
[bibtex]

Semantic and Interactive Content-based Image Retrieval
Björn Barz. 2020. Dissertation. ISBN 978-3-7369-7346-6.
[bibtex] [web]

Deep Learning on Small Datasets without Pre-Training using Cosine Loss
Björn Barz and Joachim Denzler.
IEEE Winter Conference on Applications of Computer Vision (WACV). Pages 1360-1369. 2020.
[bibtex] [pdf] [code] [abstract]

Understanding Changes in Environmental Time Series with Time-frequency Causality Analysis
Maha Shadaydeh and Yanira Guanche Garcia and Miguel Mahecha and Joachim Denzler.
European Geosciences Union General Assembly (EGU): Abstract + Poster Presentation. 2020.
[bibtex] [pdf] [web] [abstract]

Abstract: Understanding causal effect relationships between the different variables in dynamical systems is an important and challenging problem in different areas of research such as attribution of climate change, brain neural connectivity analysis, psychology, among many others. These relationships are guided by the process generating them. Hence, detecting changes or new patterns in the causal effect relationships can be used not only for the detection but also for the diagnosis and attribution of changes in the underlying process.Time series of environmental time series most often contain multiple periodical components, e.g. daily and seasonal cycles, induced by the meteorological forcing variables. This can significantly mask the underlying endogenous causality structure when using time-domain analysis and therefore results in several spurious links. Filtering these periodic components as preprocessing step might degrade causal inference. This motivates the use of time-frequency processing techniques such as Wavelet or short-time Fourier transform where the causality structure can be examined at each frequency component and on multiple time scales.In this study, we use a parametric time-frequency representation of vector autoregressive Granger causality for causal inference. We first show that causal inference using time-frequency domain analysis outperforms time-domain analysis when dealing with time series that contain periodic components, trends, or noise. The proposed approach allows for the estimation of the causal effect interaction between each pair of variables in the system on multiple time scales and hence for excluding links that result from periodic components.Second, we investigate whether anomalous events can be identified based on the observed changes in causal relationships. We consider two representative examples in environmental systems: land-atmosphere ecosystem and marine climate. Through these two examples, we show that an anomalous event can indeed be identified as the event where the causal intensities differ according to a distance measure from the average causal intensities. Two different methods are used for testing the statistical significance of the causal-effect intensity at each frequency component.Once the anomalous event is detected, the driver of the event can be identified based on the analysis of changes in the obtained causal effect relationships during the time duration of the event and consequently provide an explanation of the detected anomalous event. Current research efforts are directed towards the extension of this work by using nonlinear state-space models, both statistical and deep learning-based ones.

A Virtual "Werkstatt" for Digitization in the Sciences
Sheeba Samuel and Maha Shadaydeh and Sebastian Böcker and Bernd Brügmann and Solveig F. Bucher and Volker Deckert and Joachim Denzler and Peter Dittrich and Ferdinand von Eggeling and Daniel Güllmar and Orlando Guntinas-Lichius and Birgitta König-Ries and Frank Löffler and Lutz Maicher and Manja Marz and Mirco Migliavacca and Jürgen R. Reichenbach and Markus Reichstein and Christine Römermann and Andrea Wittig.
. 6: pages e54106. 2020.
[bibtex] [web] [abstract]

Region-based Edge Convolutions with Geometric Attributes for the Semantic Segmentation of Large-scale 3D Point Clouds
Jhonatan Contreras and Sven Sickert and Joachim Denzler.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13 (1): pages 2598-2609. 2020.
[bibtex] [pdf] [web] [abstract]

The Whole Is More Than Its Parts? From Explicit to Implicit Pose Normalization
Marcel Simon and Erik Rodner and Trevor Darell and Joachim Denzler.
IEEE Transactions on Pattern Analysis and Machine Intelligence. 42 (3): pages 749-763. 2020. (Pre-print published in 2019.)
[bibtex] [pdf] [web] [abstract]

Determining the Relevance of Features for Deep Neural Networks
Christian Reimers and Jakob Runge and Joachim Denzler.
European Conference on Computer Vision. Pages 330-346. 2020.
[bibtex] [abstract]

Towards Confirmable Automated Plant Cover Determination
Matthias Körschens and Paul Bodesheim and Christine Römermann and Solveig Franziska Bucher and Josephine Ulrich and Joachim Denzler.
ECCV Workshop on Computer Vision Problems in Plant Phenotyping (CVPPP). 2020.
[bibtex] [pdf] [web] [supplementary] [abstract]

Active and Incremental Learning with Weak Supervision
Clemens-Alexander Brust and Christoph Käding and Joachim Denzler.
Künstliche Intelligenz (KI). 2020.
[bibtex] [pdf] [abstract]

Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach
Martin Jung and Christopher Schwalm and Mirco Migliavacca and Sophia Walther and Gustau Camps-Valls and Sujan Koirala and Peter Anthoni and Simon Besnard and Paul Bodesheim and Nuno Carvalhais and Frederic Chevallier and Fabian Gans and Daniel S. Goll and Vanessa Haverd and Philipp Köhler and Kazuhito Ichii and Atul K. Jain and Junzhi Liu and Danica Lombardozzi and Julia E.M.S. Nabel and Jacob A. Nelson and Michael OSullivan and Martijn Pallandt and Dario Papale and Wouter Peters and Julia Pongratz and Christian Rödenbeck and Stephen Sitch and Gianluca Tramontana and Anthony Walker and Ulrich Weber and Markus Reichstein.
Biogeosciences. 17 (5): pages 1343-1365. 2020.
[bibtex] [pdf] [web] [abstract]

Abstract: FLUXNET comprises globally distributed eddy-covariance-based estimates of carbon fluxes between the biosphere and the atmosphere. Since eddy covariance flux towers have a relatively small footprint and are distributed unevenly across the world, upscaling the observations is necessary to obtain global-scale estimates of biosphereatmosphere exchange. Based on cross-consistency checks with atmospheric inversions, sun-induced fluorescence (SIF) and dynamic global vegetation models (DGVMs), here we provide a systematic assessment of the latest upscaling efforts for gross primary production (GPP) and net ecosystem exchange (NEE) of the FLUXCOM initiative, where different machine learning methods, forcing data sets and sets of predictor variables were employed. Spatial patterns of mean GPP are consistent across FLUXCOM and DGVM ensembles (R2>0.94 at 1 spatial resolution) while the majority of DGVMs show, for 70% of the land surface, values outside the FLUXCOM range. Global mean GPP magnitudes for 20082010 from FLUXCOM members vary within 106 and 130PgCyr1 with the largest uncertainty in the tropics. Seasonal variations in independent SIF estimates agree better with FLUXCOM GPP (mean global pixel-wise R20.75) than with GPP from DGVMs (mean global pixel-wise R20.6). Seasonal variations in FLUXCOM NEE show good consistency with atmospheric inversion-based net land carbon fluxes, particularly for temperate and boreal regions (R2>0.92). Interannual variability of global NEE in FLUXCOM is underestimated compared to inversions and DGVMs. The FLUXCOM version which also uses meteorological inputs shows a strong co-variation in interannual patterns with inversions (R2=0.87 for 20012010). Mean regional NEE from FLUXCOM shows larger uptake than inversion and DGVM-based estimates, particularly in the tropics with discrepancies of up to several hundred grammes of carbon per square metre per year. These discrepancies can only partly be reconciled by carbon loss pathways that are implicit in inversions but not captured by the flux tower measurements such as carbon emissions from fires and water bodies. We hypothesize that a combination of systematic biases in the underlying eddy covariance data, in particular in tall tropical forests, and a lack of site history effects on NEE in FLUXCOM are likely responsible for the too strong tropical carbon sink estimated by FLUXCOM. Furthermore, as FLUXCOM does not account for CO2 fertilization effects, carbon flux trends are not realistic. Overall, current FLUXCOM estimates of mean annual and seasonal cycles of GPP as well as seasonal NEE variations provide useful constraints of global carbon cycling, while interannual variability patterns from FLUXCOM are valuable but require cautious interpretation. Exploring the diversity of Earth observation data and of machine learning concepts along with improved quality and quantity of flux tower measurements will facilitate further improvements of the FLUXCOM approach overall.

Do We Train on Test Data? Purging CIFAR of Near-Duplicates
Björn Barz and Joachim Denzler.
Journal of Imaging. 6 (6): 2020.
[bibtex] [pdf] [web] [abstract]

Earth system data cubes unravel global multivariate dynamics
Miguel D. Mahecha and Fabian Gans and Gunnar Brandt and Rune Christiansen and Sarah E. Cornell and Normann Fomferra and Guido Kraemer and Jonas Peters and Paul Bodesheim and Gustau Camps-Valls and Jonathan F. Donges and Wouter Dorigo and Lina M. Estupinan-Suarez and Victor H. Gutierrez-Velez and Martin Gutwin and Martin Jung and Maria C. Londono and Diego Miralles and Phillip Papastefanou and Markus Reichstein.
Earth System Dynamics. 11 (1): pages 201-234. 2020.
[bibtex] [pdf] [web] [abstract]

EarthNet2021: A novel large-scale dataset and challenge for forecasting localized climate impacts
Christian Requena-Mesa and Vitus Benson and Joachim Denzler and Jakob Runge and Markus Reichstein.
arXiv preprint arXiv:2012.06246. 2020.
[bibtex] [web]

Exploring and Exploiting Conditioning of Reinforcement Learning Agents
Arip Asadulaev and Igor Kuznetsov and Gideon Stein and Andrey Filchenkov.
IEEE Access. 8: pages 211951-211960. 2020.
[bibtex] [abstract]

Functional outcome and quality of life after hypoglossal-facial jump nerve suture
Gerd F. Volk and Maren Geitner and Katharina Geißler and Jovanna Thielker and Ashraf Raslan and Oliver Mothes and Christian Dobel and Orlando Guntinas-Lichius.
Frontiers Surgery - Otorhinolaryngology - Head and Neck Surgery. 2020.
[bibtex] [abstract]

Automatic and Objective Facial Palsy Grading Index Prediction using Deep Feature Regression
Anish Raj and Oliver Mothes and Sven Sickert and Gerd F. Volk and Orlando Guntinas-Lichius and Joachim Denzler.
Annual Conference on Medical Image Understanding and Analysis (MIUA). Pages 253-266. 2020.
[bibtex] [pdf] [web] [abstract]

Stabilizing Transformer-Based Action Sequence Generation For Q-Learning
Gideon Stein and Andrey Filchenkov and Arip Asadulaev.
arXiv preprint 2010.12698. 2020.
[bibtex] [pdf] [abstract]

Toy models to analyze emergent constraint approaches
Xavier-Andoni Tibau and Christian Reimers and Veronika Eyring and Joachim Denzler and Markus Reichstein and Jakob Runge.
European Geosciences Union General Assembly (EGU): Abstract + Poster Presentation. 2019.
[bibtex] [pdf] [web] [abstract]

Abstract: Climate projections are limited by the arising uncertainties associated with not well-known physical processes in climate change. In every new generation, climate models improve several aspects of projections, while others remain in the same uncertainty range, especially those regarding equilibrium climate sensitivity (ECS) and climate feedbacks. Emergent constraints, defined as a 'physically explainable empirical relationships between characteristics of the current climate and long-term climate prediction that emerge in collections of climate model simulations' [1], is a promising novel approach that can shed light on climate change uncertainties and improve climate models. Since the first emergent constraint was proposed to constrain the Surface Albedo Feedback in 2006 by Hall & Qu [2], several of them have been proposed for constraining feedbacks and uncertainties of climate models, e.g., ECS, low-level cloud optical depth or tropical primary production. Emergent constraints have already been a prolific approach to improve our climate models. The typical approach to identify emergent constraints comes from expert knowledge when this is used to explore climate data and select those emergent constraints that are physically explainable. Caldwell et al. [3] presented a work where a new approach was suggested. In that paper, they attempt to identify quantities in the current climate which are skillful predictors of ECS yet can be constrained by observations. One of the main conclusions of this work was that the development of data mining methods for identifying emergent constraints should be aware of spurious emergent relations that could arise by chance. This becomes especially relevant in the next phase of the CMIP Project (6th). In the present work, we discuss simple spatiotemporal climate ("toy") models to analyze and evaluate methodologies to identify predictors for emergent constraints. Such models are simple enough to be analyzed not only empirically but also analytically, and at the same time incorporate relevant aspects of the complexity of a nonlinear dynamical spatiotemporal system. Consequently, they can be used to study assumptions and pitfalls of data mining methods for emergent constraints and guide the development of future approaches. [1]: Klein, S. A., & Hall, A. (2015). Emergent constraints for cloud feedbacks. Current Climate Change Reports, 1(4), 276-287. [2]: Hall, A., & Qu, X. (2006). Using the current seasonal cycle to constrain snow albedo feedback in future climate change. Geophysical Research Letters, 33(3). [3]: Caldwell, P. M., Bretherton, C. S., Zelinka, M. D., Klein, S. A., Santer, B. D., & Sanderson, B. M. (2014). Statistical significance of climate sensitivity predictors obtained by data mining. Geophysical Research Letters, 41(5), 1803-1808.

Deep learning and process understanding for data-driven Earth system science
Markus Reichstein and Gustau Camps-Valls and Bjorn Stevens and Martin Jung and Joachim Denzler and Nuno Carvalhais and Prabhat.
Nature. 566 (7743): pages 195-204. 2019.
[bibtex] [web] [abstract]

Integrating Domain Knowledge: Using Hierarchies to Improve Deep Classifiers
Clemens-Alexander Brust and Joachim Denzler.
Asian Conference on Pattern Recognition (ACPR). 2019.
[bibtex] [pdf] [abstract]

Not just a Matter of Semantics: The Relationship between Visual Similarity and Semantic Similarity
Clemens-Alexander Brust and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 414-427. 2019.
[bibtex] [pdf] [abstract]

Automated objective and marker-free facial grading using photographs of patients with facial palsy.
Oliver Mothes and Luise Modersohn and Gerd F. Volk and Carsten Klingner and Otto W. Witte and Peter Schlattmann and Joachim Denzler and Orlando Guntinas-Lichius.
European Archives of Oto-Rhino-Laryngology. 2019.
[bibtex] [pdf]

International Validation of an Automated Algorithm to Classify the Severity of Facial Palsy
Orlando Guntinas-Lichius and Gerd F. Volk and Joachim Denzler.
Laryngo-Rhino-Otologie. 98 (S02): pages 357-358. 2019.
[bibtex] [web]

Causal Link Estimation under Hidden Confounding in Ecological Time Series
Violeta Teodora Trifunov and Maha Shadaydeh and Jakob Runge and Veronika Eyring and Markus Reichstein and Joachim Denzler.
International Workshop on Climate Informatics (CI). 2019.
[bibtex] [pdf] [abstract]

Active Learning for Deep Object Detection
Clemens-Alexander Brust and Christoph Käding and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 181-190. 2019.
[bibtex] [pdf] [abstract]

Predicting Landscapes from Environmental Conditions Using Generative Networks
Christian Requena-Mesa and Markus Reichstein and Miguel Mahecha and Basil Kraft and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 203-217. 2019.
[bibtex] [abstract]

Machine Learning based Classification of Facial Palsies using Standard Still Photografies
Orlando Guntinas-Lichius and Oliver Mothes and Gerd F. Volk and Carsten M. Klingner and Otto W. Witte and Peter Schlattmann and Joachim Denzler.
Laryngo-Rhino-Otologie. 98 (S02): pages 360. 2019.
[bibtex] [web]

ELPephants: A Fine-Grained Dataset for Elephant Re-Identification
Matthias Körschens and Joachim Denzler.
ICCV Workshop on Computer Vision for Wildlife Conservation (ICCV-WS). 2019.
[bibtex] [pdf] [abstract]

Fetal ECG extraction exploiting joint sparse supports in a dual dictionary framework
Furrukh Sana and Tarig Ballal and Maha Shadaydeh and Ibrahim Hoteit and Tareq Y. Al-Naffouri.
Biomedical Signal Processing and Control. 48: pages 46 - 60. 2019.
[bibtex] [pdf] [web] [abstract]

One-Shot Learned Priors in Augmented Active Appearance Models for Anatomical Landmark Tracking
Oliver Mothes and Joachim Denzler.
Computer Vision, Imaging and Computer Graphics -- Theory and Applications. Pages 85-104. 2019.
[bibtex] [web] [abstract]

Automatically Estimating Forestal Characteristics in 3D Point Clouds using Deep Learning
Jhonatan Contreras and Sven Sickert and Joachim Denzler.
iDiv Annual Conference. 2019. Poster
[bibtex] [web] [abstract]

Time-Frequency Causal Inference Uncovers Anomalous Events in Environmental Systems
Maha Shadaydeh and Joachim Denzler and Yanira Guanche Garcia and Miguel Mahecha.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 499-512. 2019.
[bibtex] [pdf] [abstract]

Edge-Convolution Point Net For Semantic Segmentation Of Large-Scale Point Clouds
Jhonatan Contreras and Joachim Denzler.
IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Pages 5236-5239. 2019.
[bibtex] [web] [abstract]

Attribution of Multivariate Extreme Events
Yanira Guanche and Maha Shadaydeh and Miguel Mahecha and Joachim Denzler.
International Workshop on Climate Informatics (CI). 2019.
[bibtex] [pdf] [abstract]

Hierarchy-based Image Embeddings for Semantic Image Retrieval
Björn Barz and Joachim Denzler.
IEEE Winter Conference on Applications of Computer Vision (WACV). Pages 638-647. 2019. Best Paper Award
[bibtex] [pdf] [web] [code] [presentation] [supplementary] [abstract]

Information-Theoretic Active Learning for Content-Based Image Retrieval
Björn Barz and Christoph Käding and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 650-666. 2019.
[bibtex] [pdf] [code] [supplementary] [abstract]

Causal Inference in Nonverbal Dyadic Communication with Relevant Interval Selection and Granger Causality
Lea Müller and Maha Shadaydeh and Martin Thümmel and Thomas Kessler and Dana Schneider and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 490-497. 2019.
[bibtex] [pdf] [web] [abstract]

Classification-Specific Parts for Improving Fine-Grained Visual Categorization
Dimitri Korsch and Paul Bodesheim and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 62-75. 2019.
[bibtex] [pdf] [web] [code] [abstract]

Fully Convolutional Networks in Multimodal Nonlinear Microscopy Images for Automated Detection of Head and Neck Carcinoma: A Pilot Study
Erik Rodner and Thomas Bocklitz and Ferdinand von Eggeling and Günther Ernst and Olga Chernavskaia and Jürgen Popp and Joachim Denzler and Orlando Guntinas-Lichius.
Head \& Neck. 41 (1): pages 116-121. 2019.
[bibtex] [web] [abstract]

Longitudinale Analyse der mimischen Gesichtsmuskulatur bei Patienten mit Morbus Parkinson
Hendrik Speckamp and Tim Berning and Tino Prell and Orlando Guntinas-Lichius and Martin Thümmel and Gerd F. Volk.
Ultraschall in der Medizin - European Journal of Ultrasound (in press). 2019. Best Poster Award
[bibtex] [pdf] [web] [abstract]

Abstract: Fragestellung Anne Heinzl et al. fanden bei der standardisierten Sonographie der mimischen Muskulatur von 38 Patienten mit Parkinson Syndrom signifikant verminderte Muskelquerschnittsflächen und Muskeldynamik im Vergleich zu geschlechtsspezifischen Referenzwerten. Bei Frauen zeigte sich eine 33,12%, bei Männern eine 36,67 % verminderte Kontraktilität gegenüber den gesunden Patienten, was eine genaue Quantifizierung der Bradykinese erlaubte (Heinzl 2018). Darauf aufbauend sind jetzt longitudinale Erhebungen mittels dynamischer Sonografie und optischen 3D-Videos an Parkinson Patienten geplant. Material und Methode Erhebung hochfrequenter Ultraschall-Videos und optischer 3D-Videos von je 3 Willkürkontraktionen im medikamentösen Off und On-State bei Patienten mit M. Parkinson. Erfassung der motorischen Beeinträchtigung mittels MDS Unified Parkinson Disease Rating Scale (MDS-UPDRS) III. Ergebnisse Der klinische Schwergradscore (MDS UPDRS III) soll mit den Veränderungen der Muskeldynamik, die sonographisch als auch optisch quantifiziert werden, korreliert werden. Wir erhoffen damit Rückschlüsse auf die Schwere der Erkrankung, aber auch auf die Wirksamkeit der medikamentösen Therapie ziehen zu können. Das ursprünglich für die Diagnostik von Fazialisparesen erstelle Ultraschall-Protokoll soll für diese neue Anwendung optimiert werden. Um einen schnellen und routinemäigen Einsatz des Ultraschalls zu ermöglichen, sollen besonders geeignete Muskeln identifiziert werden. Zudem soll geklärt werden, ob auch die optischen 3D-Videos bereits ähnliche Aussagen erlauben. Schlussfolgerung Wir hoffen mittels hochfrequenter Sonographie, aber auch mit 3D-Videos erstmals die Veränderungen der Muskeldynamik von Patienten mit M. Parkinson intra-individuell quantifizieren zu können. Damit wäre das Hauptsymptom Bradykinese auch empirisch nutzbar und quantifizierbar. Dies könnte ein Werkzeug für Studien und für die empirische Optimierung der Medikation sein.

Long-term home-based Surface Electrostimulation is useful to prevent atrophy in denervated Facial Muscles
Gerd F. Volk and Martin Thümmel and Oliver Mothes and Dirk Arnold and Jovanna Thielker and Joachim Denzler and Valeria Mastryukova and Winfried Mayr and Orlando Guntinas-Lichius.
Vienna Workshop on Functional Electrical Stimulation (FESWS). 2019.
[bibtex] [pdf] [abstract]

Registration of High Resolution Sar and Optical Satellite Imagery Using Fully Convolutional Networks
Stefan Hoffmann and Clemens-Alexander Brust and Maha Shadaydeh and Joachim Denzler.
International Geoscience and Remote Sensing Symposium (IGARSS). Pages 5152-5155. 2019.
[bibtex] [pdf] [abstract]

Automated Polyp Differentiation on Coloscopic Data using Semantic Segmentation with CNNs
Marie Arlt and Jack Peter and Sven Sickert and Clemens-Alexander Brust and Joachim Denzler and Andreas Stallmach.
Endoscopy. 51 (04): pages 4. 2019.
[bibtex] [web] [abstract]

Intraoperative Online Image-guided Biopsie on the Basis of a Deep Learning Algorithm to the Automatic Detection of Head and Neck Carcinoma by Means of Real Time Near-Infrared ICG Fluorescence Endoscopy
Andreas Dittberner and Sven Sickert and Joachim Denzler and Orlando Guntinas-Lichius.
Laryngo-Rhino-Otologie. 98 (S02): pages 115. 2019.
[bibtex] [web]

LOST: A flexible framework for semi-automatic image annotation
Jonas Jäger and Gereon Reus and Joachim Denzler and Viviane Wolff and Klaus Fricke-Neuderth.
arXiv preprint arXiv:1910.07486. 2019.
[bibtex] [pdf]

Nonlinear Causal Link Estimation under Hidden Confounding with an Application to Time-Series Anomaly Detection
Violeta Teodora Trifunov and Maha Shadaydeh and Jakob Runge and Veronika Eyring and Markus Reichstein and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 261-273. 2019.
[bibtex] [pdf] [abstract]

Detecting Regions of Maximal Divergence for Spatio-Temporal Anomaly Detection
Björn Barz and Erik Rodner and Yanira Guanche Garcia and Joachim Denzler.
IEEE Transactions on Pattern Analysis and Machine Intelligence. 41 (5): pages 1088-1101. 2019. (Pre-print published in 2018.)
[bibtex] [pdf] [web] [code] [abstract]

Using Causal Inference to Globally Understand Black Box Predictors Beyond Saliency Maps
Christian Reimers and Jakob Runge and Joachim Denzler.
International Workshop on Climate Informatics (CI). 2019.
[bibtex] [pdf] [abstract]

Visibility Guided NMS: Efficient Boosting of Amodal Object Detection in Crowded Traffic Scenes
Nils Gählert and Niklas Hanselmann and Uwe Franke and Joachim Denzler.
Machine Learning for Autonomous Driving Workshop at NeurIPS (NeurIPS-WS). 2019.
[bibtex] [abstract]

Diverse Perspectives on the Relationship between Artificial Intelligence and Pattern Recognition
Björn Barz and Prerana Mukherjee and Brejesh Lall and Elham Vahdati. 2019.
[bibtex] [web] [abstract]

Self-supervised Data Bootstrapping for Deep Optical Character Recognition of Identity Documents
Oliver Mothes and Joachim Denzler.
arXiv preprint arXiv:1908.04027. 2019.
[bibtex] [pdf] [abstract]

Fusionskonzept zur Reibwertschätzung auf Basis von Wetter- und Fahrbahnzustandsinformationen
Waldemar Jarisa and Roman Henze and Ferit Kücükay and Felix Schneider and Joachim Denzler and Bernd Hartmann.
VDI-Fachtagung Reifen - Fahrwerk - Fahrbahn. 2019. Best Paper Award
[bibtex] [abstract]

Abstract: Die Fahrsicherheit ist ein zentrales Entwicklungsziel in der Automobilindustrie, welches mit dem automatisierten Fahren vor neuen Herausforderungen steht. Um die Fahrsicherheit zu gewährleisten, bedarf es einer genauen Kenntnis der unmittelbaren Fahrumgebung. Die Fahrumgebung setzt sich dabei aus mehreren Komponenten zusammen. Neben der Straentopologie und den Verkehrsteilnehmern kommt der Kenntnis über den Fahrbahnzustand, in Form von trockenen, nassen oder schnee- und eisbedeckten Straen, eine groe Bedeutung zu. Im Rahmen dieser Arbeit werden in Kooperation mit der Friedrich-Schiller-Universität Jena und beauftragt durch die Continental AG Fusionskonzepte zur Fahrbahnzustandsklassifikation entwickelt, welche den Fahrbahnzustand, respektive den Reibwert, innerhalb der Gruppen trocken, nass und winterlich differenzieren. Grundlage für die Modellentwicklung sind Messdaten einer Messkampagne (ca. 6455 km) auf realen Straen bei unterschiedlichsten Straenzuständen und Witterungsbedingungen mit einem Versuchsträger des Instituts für Fahrzeugtechnik. Dieser ist in der Lage, auf unterschiedlichen Informationsebenen, bestehend aus digitalen Wetterkarten, Umfelddaten, Kamera- und Fahrdynamikinformationen sowie optional auch Laserdaten, den Fahrbahnzustand zu klassifizieren. Dabei wird jeweils ein Klassifikationsalgorithmus auf Basis der Frontkamera- als auch der Surround-View-Kamerabilder im rechten Auenspiegel verwendet. Die aufgezeichneten Signale werden mit einander fusioniert, um einerseits die Verfügbarkeit und andererseits die Genauigkeit der Fahrbahnzustandsklassifikation zu gewährleisten. Hierzu werden die Möglichkeiten zur frühen Fusion von Kamerabildern unter Berücksichtigung von Kontextwissen, wie z. B. Luft- oder Fahrbahntemperatur mittels Deep-Learning-Ansätzen untersucht. Abschlieend wird der Zusammenhang zwischen dem tatsächlichen Fahrbahnzustand und einer maximalen Kraftschlussausnutzung anhand einer repräsentativen Anzahl von ABS-Bremsungen evaluiert.

Deep Learning is not a Matter of Depth but of Good Training
Björn Barz and Joachim Denzler.
International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI). Pages 683-687. 2018.
[bibtex] [pdf] [abstract]

Automated MRI Volumetry of the Olfactory Bulb
Niclas Schmitt and Sven Sickert and Orlando Guntinas-Lichius and Thomas Bitter and Joachim Denzler.
Laryngo-Rhino-Otologie. 97 (S02): pages 36. 2018.
[bibtex] [web] [abstract]

SMOS Vegetation Optical Depth and Ecosystem Functional Properties: Exploring Their Relationships in Tropical Forests
Gaia Vaglio Laurin and Cristina Vittucci and Gianluca Tramontana and Paul Bodesheim and Paolo Ferrazzoli and Leila Guerriero and Martin Jung and Miguel D. Mahecha and Dario Papale.
IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Pages 5891-5894. 2018.
[bibtex] [pdf] [web] [abstract]

HER2 challenge contest: a detailed assessment of automated HER2 scoring algorithms in whole slide images of breast cancer tissues
Talha Qaiser and Abhik Mukherjee and Chaitanya Reddy PB and Sai D Munugoti and Vamsi Tallam and Tomi Pitkäaho and Taina Lehtimäki and Thomas Naughton and Matt Berseth and Anibal Pedraza and Ramakrishnan Mukundan and Matthew Smith and Abhir Bhalerao and Erik Rodner and Marcel Simon and Joachim Denzler and Chao-Hui Huang and Gloria Bueno and David Snead and Ian O Ellis and Mohammad Ilyas and Nasir Rajpoot.
Histopathology. 72 (2): pages 227-238. 2018.
[bibtex] [web] [abstract]

Towards Automatic Identification of Elephants in the Wild
Matthias Körschens and Björn Barz and Joachim Denzler.
AI for Wildlife Conservation Workshop (AIWC). 2018.
[bibtex] [pdf] [abstract]

Discovering unknown visual objects with novelty detection techniques
Paul Bodesheim. 2018. Dissertation. ISBN: 978-3-8439-3546-3
[bibtex] [web] [abstract]

On the Relation Between Artifical Intelligence and Pattern Recognition
Björn Barz.
ICPRAI 2018 Competition. 2018. Award-winning Entry
[bibtex] [pdf]

Domain knowledge integration for causality analysis of carbon-cycle variables
Violeta Teodora Trifunov and Maha Shadaydeh and Jakob Runge and Veronika Eyring and Markus Reichstein and Joachim Denzler.
American Geophysical Union Fall Meeting (AGU): Abstract + Poster Presentation. 2018.
[bibtex] [web] [abstract]

Enhancing Flood Impact Analysis using Interactive Retrieval of Social Media Images
Björn Barz and Kai Schröter and Moritz Münch and Bin Yang and Andrea Unger and Doris Dransch and Joachim Denzler.
Archives of Data Science, Series A. 5 (1): pages A06, 21 S. online. 2018.
[bibtex] [pdf] [abstract]

Keeping the Human in the Loop: Towards Automatic Visual Monitoring in Biodiversity Research
Joachim Denzler and Christoph Käding and Clemens-Alexander Brust.
International Conference on Ecological Informatics (ICEI). Pages 16. 2018.
[bibtex] [abstract]

Abstract: More and more methods in the area of biodiversity research grounds upon new opportunities arising from modern sensing devices that in principle make it possible to continuously record sensor data from the environment. However, these opportunities allow easy recording of huge amount of data, while its evaluation is difficult, if not impossible due to the enormous effort of manual inspection by the researchers. At the same time, we observe impressive results in computer vision and machine learning that are based on two major developments: firstly, the increased performance of hardware together with the advent of powerful graphical processing units applied in scientific computing. Secondly, the huge amount of, in part, annotated image data provided by today's generation of Facebook and Twitter users that are available easily over databases (e.g., Flickr) and/or search engines. However, for biodiversity applications appropriate data bases of annotated images are still missing. In this presentation we discuss already available methods from computer vision and machine learning together with upcoming challenges in automatic monitoring in biodiversity research. We argue that the key element towards success of any automatic method is the possibility to keep the human in the loop - either for correcting errors and improving the system's quality over time, for providing annotation data at moderate effort, or for acceptance and validation reasons. Thus, we summarize already existing techniques from active and life-long learning together with the enormous developments in automatic visual recognition during the past years. In addition, to allow detection of the unexpected such an automatic system must be capable to find anomalies or novel events in the data. We discuss a generic framework for automatic monitoring in biodiversity research which is the result of collaboration between computer scientists and ecologists of the past years. The key ingredients of such a framework are initial, generic classifier, for example, powerful deep learning architectures, active learning to reduce costly annotation effort by experts, fine-grained recognition to differentiate between visually very similar species, and efficient incremental update of the classifier's model over time. For most of these challenges, we present initial solutions in sample applications. The results comprise the automatic evaluation of images from camera traps, attribute estimation for species, as well as monitoring in-situ data in environmental science. Overall, we like to demonstrate the potentials and open issues in bringing together computer scientists and ecologist to open new research directions for either area.

Aquaplaning - a potential hazard also for Automated Driving
Bernd Hartmann and Thomas Raste and Matthias Kretschmann and Manuel Amthor and Felix Schneider and Joachim Denzler.
ITS automotive nord e.V. (Hrsg.), Braunschweig. 2018.
[bibtex]

Facial motor and non-motor disabilities in patients with central facial paresis: a prospective cohort study
Gerd F. Volk and Anika Steinerstauch and Annegret Lorenz and Luise Modersohn and Oliver Mothes and Joachim Denzler and Carsten M. Klingner and Farsin Hamzei and Orlando Guntinas-Lichius.
Journal of Neurology. 2018.
[bibtex]

SupernoVAE: Using deep learning to find spatio-temporal dynamics in Earth system data
Xavier-Andoni Tibau and Christian Requena-Mesa and Christian Reimers and Joachim Denzler and Veronika Eyring and Markus Reichstein and Jakob Runge.
American Geophysical Union Fall Meeting (AGU): Abstract + Poster Presentation. 2018.
[bibtex] [web] [abstract]

Abstract: Exploring and understanding spatio-temporal patterns on Earth system datasets is one of the principal goals of the climate and geo-science communities. In this direction, Empirical Orthogonal Functions (EOFs) have been used to characterize phenomena such as the El Nino Southern Oscillation, the Arctic jet stream or the Indian Monsoon. However, EOF analysis has several limitations, for example, it can only identify linear and orthogonal patterns. We present a framework that makes use of a convolutional variational autoencoder (VAE) as a learnable feature function to extract spatio-temporal dynamics via PCA. The VAE encodes the information in an abstract space of higher order features representing different patterns. Over this space, PCA is performed to obtain a spatial representation of related temporal dynamics. We have used three datasets, two artificial datasets where the dynamics are ruled by a hidden spatially varying parameter and an observational reanalysis dataset of monthly sea surface temperature from 1898 to 2014. The artificial datasets have chaotic and, chaotic and stochastic dynamics depending on the spatial hidden parameter. As baseline methods, EOF analysis and Kernel PCA were performed over the original spaces. For the two artificial datasets, we found a high correlation between some of the first Principal Components on the feature space and the spatial hidden parameter. This correlation was not found using baseline methods in the original space. In the reanalysis dataset, the method was able to find known modes, such as ENSO, as well as other patterns that baseline methods did not reveal that might have inmmediate effect on how we understand the earth system after expert interpretation. These results provide a proof of concept: SupernoVAE is not only able to extract well-known climate patterns previously characterized with linear EOF analysis, but also allows to extract non-linear and non-orthogonal patterns that can help in analyzing Earth system dynamics that could not be characterized before.

SupernoVAE: VAE based Kernel-PCA for Analysis of Spatio-Temporal Earth Data
Xavier-Andoni Tibau and Christian Requena-Mesa and Christian Reimers and Joachim Denzler and Veronika Eyring and Markus Reichstein and Jakob Runge.
International Workshop on Climate Informatics (CI). Pages 73-76. 2018.
[bibtex] [web] [abstract]

Analyzing the Time Variant Causality in Ecological Time Series: A Time-Frequency Approach
Maha Shadaydeh and Yanira Guanche Garcia and Miguel Mahecha and Markus Reichstein and Joachim Denzler.
International Conference on Ecological Informatics (ICEI). Pages 151-152. 2018.
[bibtex] [abstract]

Abstract: Attribution in ecosystems aims to identify the cause-effect relationships between the variables involved. The availability of high temporal resolution data along with the powerful computing platforms further enhance the capacity of data-driven methods in capturing the complex relationships between the variables of the underlying system. Time series of ecological variables most often contain different periodical components that can significantly mask the underling causality structure in time domain. This motivates the use of time-frequency processing techniques such as wavelet analysis or short time Fourier transform. In this study we present a time-frequency approach for causality analysis where the coupling between the variables is assumed to follow a locally time-invariant multivariate autoregressive (MVAR) model. We propose a sliding time window approach to examine the change of interactions, i.e. direction and strength of causality, between the different variables over seasons. The cause-effect relationships are extracted using the frequency domain representation of the MVAR Granger causality (MVAR-GC) [1,2] based on the generalized partial directed coherence (gPDC) [3]. We have first applied the proposed method to synthetic data to evaluate its sensitivity to different issues such as the selection of the model order, the sampling frequency, the absence of cause as well as the presence of non-linear coupling. The method is then applied to half-hourly meteorological observations and land flux eddy covariance data to investigate the causal-effect relationships between global radiation (Rg), air temperature (Tair), and the CO2 land fluxes: gross primary productivity (GPP), net ecosystem exchange (NEE) and ecosystem respiration (Reco). The results show that time-frequency analysis based on MVAR-GC has promising potential in identifying the time variant causality structure within these variables along with the main time delay between different cause- effect pairs. Further research work is currently going for the investigation of the selection criteria of the model order, the sampling frequency, and the size of the time window at different time scales of causality analysis. This study is carried out within the framework of the project BACI which in part aims at developing an attribution scheme for changes in ecosystem functioning and studying the impacts of these changes on biodiversity patterns.

BACI: Towards a Biosphere Atmosphere Change Index - Detection of Extreme Events in the Biosphere
Yanira Guanche Garcia and Maha Shadaydeh and Miguel Mahecha and Markus Reichstein and Joachim Denzler.
BigSkyEarth Conference: AstroGeoInformatics. 2018.
[bibtex] [pdf] [web]

Putting User Reputation on the Map: Unsupervised Quality Control for Crowdsourced Historical Data
Björn Barz and Thomas C. van Dijk and Bert Spaan and Joachim Denzler.
2nd ACM SIGSPATIAL Workshop on Geospatial Humanities. Pages 3:1-3:6. 2018.
[bibtex] [pdf] [abstract]

Classification of Spatiotemporal Marine Climate Patterns using Wavelet Coherence and Markov Random Field
Maha Shadaydeh and Yanira Guanche Garcia and Joachim Denzler.
American Geophysical Union Fall Meeting (AGU): Abstract + Oral Presentation. 2018.
[bibtex] [web] [abstract]

Abstract: Sea condition characterization and classification is a widely studied topic but rather challenging one due to the spatial and temporal variability in marine climate. The aim of this study is to develop a data-driven method for the classification of marine climate patterns. The proposed method consists of two main steps: i) Feature extraction applied to the time series of each point of the grid independently. ii) Spatiotemporal classification applied on the obtained features over the entire study area. The causal intensity between coupled marine variables can be efficiently visualized at different time-scales using wavelet coherence. To this end, we extract a set of features from the statistically significant wavelet coherence of each pair of the used marine variables: significant wave height (hs), mean wave period (Tm), and wave direction (m). The obtained features, in addition to the sea level pressure (SLP), over the entire study area are then treated as multi-channel images. For the spatiotemporal classification of these images, we first apply the unsupervised K-means clustering method on the images of each three consecutive time instances. The K clusters represent K different marine climate patterns. Markov Random Fields (MRFs) provide an effective methodology for integrating spatiotemporal dependency between adjacent points into the image classification process. In this study, we use a MRF model for defining the spatiotemporal extent of the detected marine climate patterns, with the statistics of the detected K clusters used for the initial training. Experimental results show that the proposed method allows for a practical classification of marine climate into representative patterns that can be used for an accurate characterization of sea conditions, the analysis of extreme events and its impacts along the coast. A case study in the North Sea will be presented using the coasDat dataset [1]. [1] Weisse, R., H. v. Storch, U. Callies, A. Chrastansky, F. Feser, I. Grabemann, H. Guenther, A. Pluess, Th. Stoye, J. Tellkamp, J. Winterfeldt and K. Woth, (2008): Regional meteo-marine reanalyses and climate change projections: Results for Northern Europe and potentials for coastal and offshore applications. Bull. Amer. Meteor. Soc., 90, 849-860.

Automatic Query Image Disambiguation for Content-Based Image Retrieval
Björn Barz and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 249-256. 2018.
[bibtex] [pdf] [code] [abstract]

When tree rings go global: challenges and opportunities for retro-and prospective insight
Flurin Babst and Paul Bodesheim and Noah Charney and Andrew D. Friend and Martin P. Girardin and Stefan Klesse and David J.P. Moore and Kristina Seftigen and Jesper Björklund and Olivier Bouriaud and Andria Dawson and R. Justin DeRose and Michael C. Dietze and Annemarie H. Eckes and Brian Enquist and David C. Frank and Miguel D. Mahecha and Benjamin Poulter and Sydne Record and Valerie Trouet and Rachael H. Turton and Zhen Zhang and Margaret E.K. Evans.
Quaternary Science Reviews. 197: pages 1-20. 2018.
[bibtex] [pdf] [web] [abstract]

Dataless Black-Box Model Comparison
Christoph Theiß and Clemens-Alexander Brust and Joachim Denzler.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 28 (4): pages 676-683. 2018. (also published at ICPRAI 2018)
[bibtex] [abstract]

Development of an Automatic Image Analysis Method by Deep Learning Methods for the Detection of Head and Neck Cancer Based on Standard Real-Time Near-Infrared ICG Fluorescence Endoscopy Images (NIR-ICG-FE)
Andreas Dittberner and Sven Sickert and Joachim Denzler and Orlando Guntinas-Lichius and Thomas Bitter and Sven Koscielny.
Laryngo-Rhino-Otologie. 97 (S02): pages 97. 2018.
[bibtex] [web] [abstract]

Active Learning for Regression Tasks with Expected Model Output Changes
Christoph Käding and Erik Rodner and Alexander Freytag and Oliver Mothes and Björn Barz and Joachim Denzler.
British Machine Vision Conference (BMVC). 2018.
[bibtex] [pdf] [code] [supplementary] [abstract]

Extreme anomaly event detection in biosphere using linear regression and a spatiotemporal MRF model
Yanira Guanche Garcia and Maha Shadaydeh and Miguel Mahecha and Joachim Denzler.
Natural Hazards. pages 1-19. 2018.
[bibtex] [pdf] [web] [abstract]

Abstract: Detecting abnormal events within time series is crucial for analyzing and understanding the dynamics of the system in many research areas. In this paper, we propose a methodology to detect these anomalies in multivariate environmental data. Five biosphere variables from a preliminary version of the Earth System Data Cube have been used in this study: Gross Primary Productivity, Latent Energy, Net Ecosystem Exchange, Sensible Heat and Terrestrial Ecosystem Respiration. To tackle the spatiotemporal dependencies of the biosphere variables, the proposed methodology after preprocessing the data is divided into two steps: a feature extraction step applied to each time series in the grid independently, followed by a spatiotemporal event detection step applied to the obtained novelty scores over the entire study area. The first step is based on the assumption that the time series of each variable can be represented by an autoregressive moving average (ARMA) process, and the anomalies are those time instances that are not well represented by the estimated ARMA model. The Mahalanobis distance of the ARMA models multivariate residuals is used as a novelty score. In the second step, the obtained novelty scores of the entire study are treated as time series of images. Markov random fields (MRFs) provide an effective and theoretically well-established methodology for integrating spatiotemporal dependency into the classification of image time series. In this study, the classification of the novelty score images into three classes, intense anomaly, possible anomaly, and normal, is performed using unsupervised K-means clustering followed by multi-temporal MRF segmentation applied recursively on the images of each consecutive $L \ge $ 1 time steps. The proposed methodology was applied to an area covering Europe and Africa. Experimental results and validation based on known historic events show that the method is able to detect historic events and also provides a useful tool to define sensitive regions.

Upscaled diurnal cycles of land-atmosphere fluxes: a new global half-hourly data product
Paul Bodesheim and Martin Jung and Fabian Gans and Miguel D. Mahecha and Markus Reichstein.
Earth System Science Data. 10 (3): pages 1327-1365. 2018.
[bibtex] [pdf] [web] [abstract]

Abstract: Interactions between the biosphere and the atmosphere can be well characterized by fluxes between the two. In particular, carbon and energy fluxes play a major role in understanding biogeochemical processes on an ecosystem level or global scale. However, the fluxes can only be measured at individual sites, e.g., by eddy covariance towers, and an upscaling of these local observations is required to analyze global patterns. Previous work focused on upscaling monthly, 8-day, or daily average values, and global maps for each flux have been provided accordingly. In this paper, we raise the upscaling of carbon and energy fluxes between land and atmosphere to the next level by increasing the temporal resolution to subdaily timescales. We provide continuous half-hourly fluxes for the period from 2001 to 2014 at 0.5 spatial resolution, which allows for analyzing diurnal cycles globally. The data set contains four fluxes: gross primary production (GPP), net ecosystem exchange (NEE), latent heat (LE), and sensible heat (H). We propose two prediction approaches for the diurnal cycles based on large-scale regression models and compare them in extensive cross-validation experiments using different sets of predictor variables. We analyze the results for a set of FLUXNET tower sites showing the suitability of our approaches for this upscaling task. Finally, we have selected one approach to calculate the global half-hourly data products based on predictor variables from remote sensing and meteorology at daily resolution as well as half-hourly potential radiation. In addition, we provide a derived product that only contains monthly average diurnal cycles, which is a lightweight version in terms of data storage that still allows studying the important characteristics of diurnal patterns globally. We recommend to primarily use these monthly average diurnal cycles, because they are less affected by the impacts of day-to-day variation, observation noise, and short-term fluctuations on subdaily timescales compared to the full half-hourly flux products. The global half-hourly data products are available at <a href="https://doi.org/10.17871/BACI.224">https://doi.org/10.17871/BACI.224</a>.

Multi-view Anatomical Animal Landmark Localization using Deep Feature Regression
Oliver Mothes and Joachim Denzler.
ICPR Workshop on Visual Observation and Analysis of Vertebrate And Insect Behavior (ICPR-WS). 2018.
[bibtex]

In Defense of Active Part Selection for Fine-Grained Classification
Dimitri Korsch and Joachim Denzler.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 28 (4): pages 658-663. 2018.
[bibtex] [pdf] [web] [abstract]

Causality analysis of ecological time series: a time-frequency approach
Maha Shadaydeh and Yanira Guanche Garcia and Miguel Mahecha and Markus Reichstein and Joachim Denzler.
International Workshop on Climate Informatics (CI). 2018.
[bibtex] [pdf]

Towards Unconstrained Content Recognition of Additional Traffic Signs
Thomas Wenzel and Steffen Brueggert and Joachim Denzler.
IEEE Intelligent Vehicles Symposium (IV). Pages 1421-1427. 2017.
[bibtex] [web] [abstract]

Underwater and in the Cloud: Web-based Machine Learning for Fish Video Analysis
Jonas Jäger and Claudia Kruschel and Stewart T. Schultz and Dubravko Pedjo and Viviane Wolff and Klaus Fricke-Neuderth and Joachim Denzler.
52nd European Marine Biology Symposium. 2017.
[bibtex] [pdf]

Predicting Carbon Dioxide and Energy Fluxes with Empirical Approaches in FLUXNET
Gianluca Tramontana and Martin Jung and Christopher R. Schwalm and Kazuhito Ichii and Gustau Camps-Valls and Botond Raduly and Markus Reichstein and M. Altaf Arain and Alessandro Cescatti and Gerard Kiely and Lutz Merbold and Penelope Serrano-Ortiz and Sven Sickert and Sebastian Wolf and Dario Papale.
European Geosciences Union General Assembly (EGU): Abstract + Poster Presentation. 2017.
[bibtex] [pdf] [web]

Image denoising via collaborative support-agnostic recovery
Muzammil Behzad and Mudassir Masood and Tarig Ballal and Maha Shadaydeh and Tareq. Y. Al-Naffouri.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Pages 1343-1347. 2017.
[bibtex] [web] [abstract]

Unsupervised Group Activity Detection by Hierarchical Dirichlet Processes
Ali Al-Raziqi and Joachim Denzler.
International Conference on Image Analysis and Recognition (ICIAR). Pages 399-407. 2017.
[bibtex] [pdf] [web] [abstract]

Modelling ocean parameters through Graphical Models
Felix Schneider and Yanira Guanche and Joachim Denzler.
MTS/IEEE OCEANS Conference Aberdeen. Pages 1-6. 2017.
[bibtex] [pdf]

You Have To Look More Than Once: Active and Continuous Exploration using YOLO
Clemens-Alexander Brust and Christoph Käding and Joachim Denzler.
CVPR Workshop on Continuous and Open-Set Learning (CVPR-WS). 2017. Poster presentation and extended abstract
[bibtex] [abstract]

Upscaling diurnal cycles of carbon fluxes
Paul Bodesheim and Martin Jung and Miguel D. Mahecha and Markus Reichstein.
European Geosciences Union General Assembly (EGU): Abstract + Poster Presentation. 2017.
[bibtex] [pdf] [web] [abstract]

Wetland mapping by fusion of airborne laser scanning and multi-temporal multispectral satellite imagery
Maha Shadaydeh and Andras Zlinszky and Andrea Manno-Kovacs and Tamas Sziranyi.
International Journal of Remote Sensing. 38 (23): pages 7422-7440. 2017.
[bibtex] [pdf] [web] [abstract]

Large-Scale Gaussian Process Inference with Generalized Histogram Intersection Kernels for Visual Recognition Tasks
Erik Rodner and Alexander Freytag and Paul Bodesheim and Björn Fröhlich and Joachim Denzler.
International Journal of Computer Vision (IJCV). 121 (2): pages 253-280. 2017.
[bibtex] [pdf] [web] [abstract]

Finding the Unknown: Novelty Detection with Extreme Value Signatures of Deep Neural Activations
Alexander Schultheiss and Christoph Käding and Alexander Freytag and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 226-238. 2017.
[bibtex] [pdf] [supplementary] [abstract]

Visual Fish Tracking: Combining a Two-Stage Graph Approach with CNN-Features
Jonas Jäger and Oliver Mothes and Viviane Wolff and Klaus Fricke-Neuderth and Joachim Denzler.
MTS/IEEE OCEANS Conference Aberdeen. Pages 1-6. 2017.
[bibtex] [pdf] [web]

Multi-marker tracking for large-scale X-ray stereo video data
Xiaoyan Jiang and Marcel Simon and Yuan Yang and Joachim Denzler.
Signal Processing: Image Communication. 59 (Supplement C): pages 140 - 149. 2017.
[bibtex] [web]

Generalized orderless pooling performs implicit salient matching
Marcel Simon and Yang Gao and Trevor Darrell and Joachim Denzler and Erik Rodner.
International Conference on Computer Vision (ICCV). Pages 4970-4979. 2017.
[bibtex] [pdf]

From Corners To Rectangles Directional Road Sign Detection Using Learned Corner Representations
Thomas Wenzel and Ta-Wei Chou and Steffen Brueggert and Joachim Denzler.
IEEE Intelligent Vehicles Symposium (IV). Pages 1039-1044. 2017.
[bibtex] [web] [abstract]

Fast Learning and Prediction for Object Detection using Whitened CNN Features
Björn Barz and Erik Rodner and Christoph Käding and Joachim Denzler.
arXiv preprint arXiv:1704.02930. 2017.
[bibtex] [pdf] [web]

Video Instruction for Synchronous Video Recording of Mimic Movement of Patients with Facial Palsy
Rebecca Anna Schaede and Gerd F. Volk and Luise Modersohn and Jodie M. Barth and Joachim Denzler and Orlando Guntinas-Lichius.
Laryngo-Rhino-Otologie. 2017.
[bibtex] [web] [abstract]

Towards Automated Visual Monitoring of Individual Gorillas in the Wild
Clemens-Alexander Brust and Tilo Burghardt and Milou Groenenberg and Christoph Käding and Hjalmar Kühl and Marie Manguette and Joachim Denzler.
ICCV Workshop on Visual Wildlife Monitoring (ICCV-WS). Pages 2820-2830. 2017.
[bibtex] [pdf] [abstract]

A Feedback Estimation Approach for Therapeutic Facial Training
Cornelia Dittmar and Joachim Denzler and Horst-Michael Gross.
IEEE International Conference on Automatic Face and Gesture Recognition (FG). Pages 141-148. 2017.
[bibtex] [abstract]

Multivariate anomaly detection for Earth observations: a comparison of algorithms and feature extraction techniques
Milan Flach and Fabian Gans and Alexander Brenning and Joachim Denzler and Markus Reichstein and Erik Rodner and Sebastian Bathiany and Paul Bodesheim and Yanira Guanche and Sebasitan Sippel and Miguel D. Mahecha.
Earth System Dynamics. 8 (3): pages 677-696. 2017.
[bibtex] [pdf] [web] [abstract]

Abstract: Today, many processes at the Earth's surface are constantly monitored by multiple data streams. These observations have become central to advancing our understanding of vegetation dynamics in response to climate or land use change. Another set of important applications is monitoring effects of extreme climatic events, other disturbances such as fires, or abrupt land transitions. One important methodological question is how to reliably detect anomalies in an automated and generic way within multivariate data streams, which typically vary seasonally and are interconnected across variables. Although many algorithms have been proposed for detecting anomalies in multivariate data, only a few have been investigated in the context of Earth system science applications. In this study, we systematically combine and compare feature extraction and anomaly detection algorithms for detecting anomalous events. Our aim is to identify suitable workflows for automatically detecting anomalous patterns in multivariate Earth system data streams. We rely on artificial data that mimic typical properties and anomalies in multivariate spatiotemporal Earth observations like sudden changes in basic characteristics of time series such as the sample mean, the variance, changes in the cycle amplitude, and trends. This artificial experiment is needed as there is no "gold standard" for the identification of anomalies in real Earth observations. Our results show that a well-chosen feature extraction step (e.g., subtracting seasonal cycles, or dimensionality reduction) is more important than the choice of a particular anomaly detection algorithm. Nevertheless, we identify three detection algorithms (k-nearest neighbors mean distance, kernel density estimation, a recurrence approach) and their combinations (ensembles) that outperform other multivariate approaches as well as univariate extreme-event detection methods. Our results therefore provide an effective workflow to automatically detect anomalies in Earth system science data.

Anatomical Landmark Tracking by One-shot Learned Priors for Augmented Active Appearance Models
Oliver Mothes and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 246-254. 2017.
[bibtex] [pdf] [web]

Life-long Learning with Applications in Monitoring Biodiversity
Joachim Denzler.
Dagstuhl Reports. 7 (2): pages 120-122. 2017.
[bibtex] [web]

Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning
Marc Aubreville and Christian Knipfer and Nicolai Oetter and Christian Jaremenko and Erik Rodner and Joachim Denzler and Christopher Bohr and Helmut Neumann and Florian Stelzle and Andreas Maier.
Scientific Reports. 7 (1): pages 41598-017. 2017.
[bibtex] [web]

Semantic Segmentation of Outdoor Areas using 3D Moment Invariants and Contextual Cues
Sven Sickert and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 165-176. 2017.
[bibtex] [pdf] [abstract]

Emergent Techniques and Applications for Big Visual Data
Zhijun Fang and Jenq-Neng Hwang and Xiaoming Huo and Hyo-Jong Lee and Joachim Denzler.
International Journal of Digital Multimedia Broadcasting. 2017: pages 2. 2017. Article ID 6468502
[bibtex] [web]

Improved tree-ring archives will support earth-system science
Flurin Babst and Benjamin Poulter and Paul Bodesheim and Miguel D. Mahecha and David C. Frank.
Nature Ecology \& Evolution. 1 (2): 2017.
[bibtex] [pdf] [web] [abstract]

When tree rings go global: challenges and opportunities for retro- andprospective insights
Flurin Babst and Olivier Bouriaud and Benjamin Poulter and Zhen Zhang and Valerie Trouet and Margaret Evans and Noah Charney and Sydne Record and Brian Enquist and Kristina Seftigen and Jesper Björklund and Stefan Klesse and Paul Bodesheim and Miguel Mahecha and Martin Girardin and Andrew Friend and David Frank.
European Geosciences Union General Assembly (EGU): Abstract + Oral Presentation. 2017.
[bibtex] [pdf] [web] [abstract]

Deep bilinear features for Her2 scoring in digital pathology
Erik Rodner and Marcel Simon and Joachim Denzler.
Current Directions in Biomedical Engineering. 3 (2): pages 811-814. 2017.
[bibtex] [pdf]

Why Computer Science needs to meet Ecology
Gustau Camps-Valls and Benjamin Adams and Joachim Denzler and Thomas Hickler and Birgitta König-Ries and Markus Reichstein and Johann Wolfgang Wägele.
Dagstuhl Reports. 7 (2): pages 114-120. 2017.
[bibtex] [web]

Maximally Divergent Intervals for Extreme Weather Event Detection
Björn Barz and Yanira Guanche and Erik Rodner and Joachim Denzler.
MTS/IEEE OCEANS Conference Aberdeen. Pages 1-9. 2017.
[bibtex] [pdf] [abstract]

Biosphere Anomalies Detection by Regression Models
Yanira Guanche and Maha Shadaydeh and Miguel Mahecha and Joachim Denzler.
Conference on Advances in Extreme Value Analysis and Application to Natural Hazards (EVAN). 2017.
[bibtex] [pdf]

Potential of new machine learning methods for understanding long-term interannual variability of carbon and energy fluxes and states from site to global scale
Markus Reichstein and Martin Jung and Paul Bodesheim and Miguel D. Mahecha and Fabian Gans and Erik Rodner and Gustau Camps-Valls and Dario Papale and Gianluca Tramontana and Joachim Denzler and Dennis D. Baldocchi.
American Geophysical Union Fall Meeting (AGU): Abstract + Oral Presentation. 2016.
[bibtex] [web] [abstract]

Predicting Carbon Dioxide and Energy Fluxes Across Global FLUXNET Sites with Regression Algorithms
Gianluca Tramontana and Martin Jung and Christopher R. Schwalm and Kazuhito Ichii and Gustau Camps-Valls and Botond Raduly and Markus Reichstein and M. Altaf Arain and Alessandro Cescatti and Gerard Kiely and Lutz Merbold and Penelope Serrano-Ortiz and Sven Sickert and Sebastian Wolf and and Dario Papale.
Biogeosciences. 13 (14): pages 4291-4313. 2016.
[bibtex] [web] [abstract]

A Novel Computerized Cell Count Algorithm for Biofilm Analysis
Mareike Klinger-Strobel and Herbert Süße and Dagmar Fischer and Mathias W. Pletz and Oliwia Makarewicz.
PLoS ONE. 11 (5): 2016.
[bibtex] [web] [abstract]

Abstract: Biofilms are the preferred sessile and matrix-embedded life form of most microorganisms on surfaces. In the medical field, biofilms are a frequent cause of treatment failure because they protect the bacteria from antibiotics and immune cells. Antibiotics are selected according to the minimal inhibitory concentration (MIC) based on the planktonic form of bacteria. Determination of the minimal biofilm eradicating concentration (MBEC), which can be up to 1,000-fold greater than the MIC, is not currently conducted as routine diagnostic testing, primarily because of the methodical hurdles of available biofilm assessing protocols that are time- and cost-consuming. Comparative analysis of biofilms is also limited as most quantitative methods such as crystal violet staining are indirect and highly imprecise. In this paper, we present a novel algorithm for assessing biofilm resistance to antibiotics that overcomes several of the limitations of alternative methods. This algorithm aims for a computer-based analysis of confocal microscope 3D images of biofilms after live/dead stains providing various biofilm parameters such as numbers of viable and dead cells and their vertical distributions within the biofilm, or biofilm thickness. The performance of this algorithm was evaluated using computer-simulated 2D and 3D images of coccal and rodent cells varying different parameters such as cell density, shading or cell size. Finally, genuine biofilms that were untreated or treated with nitroxoline or colistin were analyzed and the results were compared with quantitative microbiological standard methods. This novel algorithm allows a direct, fast and reproducible analysis of biofilms after live/dead staining. It performed well in biofilms of moderate cell densities in a 2D set-up however the 3D analysis remains still imperfect and difficult to evaluate. Nevertheless, this is a first try to develop an easy but conclusive tool that eventually might be implemented into routine diagnostics to determine the MBEC and to improve outcomes of patients with biofilm-associated infections.

Fully automated tracking of cardiac structures using radiopaque markers and high-frequency videofluoroscopy in an in vivo ovine model: from three-dimensional marker coordinates to quantitative analyses
Wolfgang Bothe and Harald Schubert and Mahmoud Diab and Gloria Faerber and Christoph Bettag and Xiaoyan Jiang and Martin S. Fischer and Joachim Denzler and Torsten Doenst.
SpringerPlus. 5 (1): 2016.
[bibtex] [pdf] [abstract]

Additional Traffic Sign Detection Using Learned Corner Representations
Thomas Wenzel and Steffen Brueggert and Joachim Denzler.
IEEE Intelligent Vehicles Symposium (IV). Pages 316-321. 2016.
[bibtex] [web] [abstract]

Using Statistical Process Control for detecting anomalies in multivariate spatiotemporal Earth Observations
Milan Flach and Miguel Mahecha and Fabian Gans and Erik Rodner and Paul Bodesheim and Yanira Guanche-Garcia and Alexander Brenning and Joachim Denzler and Markus Reichstein.
European Geosciences Union General Assembly (EGU): Abstract + Oral Presentation. 2016.
[bibtex] [pdf] [web] [abstract]

Abstract: The number of available Earth observations (EOs) is currently substantially increasing. Detecting anomalous pat-terns in these multivariate time series is an important step in identifying changes in the underlying dynamicalsystem. Likewise, data quality issues might result in anomalous multivariate data constellations and have to beidentified before corrupting subsequent analyses. In industrial application a common strategy is to monitor pro-duction chains with several sensors coupled to some statistical process control (SPC) algorithm. The basic ideais to raise an alarm when these sensor data depict some anomalous pattern according to the SPC, i.e. the produc-tion chain is considered out of control. In fact, the industrial applications are conceptually similar to the on-linemonitoring of EOs. However, algorithms used in the context of SPC or process monitoring are rarely consideredfor supervising multivariate spatio-temporal Earth observations. The objective of this study is to exploit the poten-tial and transferability of SPC concepts to Earth system applications. We compare a range of different algorithmstypically applied by SPC systems and evaluate their capability to detect e.g. known extreme events in land sur-face processes. Specifically two main issues are addressed: (1) identifying the most suitable combination of datapre-processing and detection algorithm for a specific type of event and (2) analyzing the limits of the individual ap-proaches with respect to the magnitude, spatio-temporal size of the event as well as the datas signal to noise ratio.Extensive artificial data sets that represent the typical properties of Earth observations are used in this study. Ourresults show that the majority of the algorithms used can be considered for the detection of multivariate spatiotem-poral events and directly transferred to real Earth observation data as currently assembled in different projectsat the European scale, e.g. http://baci-h2020.eu/index.php/ and http://earthsystemdatacube.net/. Known anomaliessuch as the Russian heatwave are detected as well as anomalies which are not detectable with univariate methods.

SeaCLEF 2016: Object Proposal Classification for Fish Detection in Underwater Videos
Jonas Jäger and Erik Rodner and Joachim Denzler and Viviane Wolff and Klaus Fricke-Neuderth.
Working Notes of CLEF 2016 - Conference and Labs of the Evaluation forum. Pages 481-489. 2016.
[bibtex] [pdf]

Impatient DNNs - Deep Neural Networks with Dynamic Time Budgets
Manuel Amthor and Erik Rodner and Joachim Denzler.
British Machine Vision Conference (BMVC). 2016.
[bibtex] [pdf]

Unsupervised Framework for Interactions Modeling between Multiple Objects
Ali Al-Raziqi and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 509-516. 2016.
[bibtex] [pdf] [abstract]

Maximally Divergent Intervals for Anomaly Detection
Erik Rodner and Björn Barz and Yanira Guanche and Milan Flach and Miguel Mahecha and Paul Bodesheim and Markus Reichstein and Joachim Denzler.
Workshop on Anomaly Detection (ICML-WS). 2016. Best Paper Award
[bibtex] [pdf] [web] [code] [abstract]

Active and Continuous Exploration with Deep Neural Networks and Expected Model Output Changes
Christoph Käding and Erik Rodner and Alexander Freytag and Joachim Denzler.
NIPS Workshop on Continual Learning and Deep Networks (NIPS-WS). 2016.
[bibtex] [pdf] [web] [abstract]

Detection of Dog-Robot Interactions in Video Sequences
Ali Al-Raziqi and Mahesh Venkata Krishna and Joachim Denzler.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 26 (1): pages 46-54. 2016.
[bibtex] [pdf] [abstract]

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers
Sebastian Sippel and Holger Lange and Miguel D. Mahecha and Michael Hauhs and Paul Bodesheim and Thomas Kaminski and Fabian Gans and Osvaldo A. Rosso.
PLOS ONE. 11 (10): pages 1-29. 2016.
[bibtex] [pdf] [web] [abstract]

Abstract: Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. We demonstrate here that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.

ImageNet pre-trained models with batch normalization
Marcel Simon and Erik Rodner and Joachim Denzler.
arXiv preprint 1612.01452. 2016.
[bibtex] [pdf] [web] [abstract]

Watch, Ask, Learn, and Improve: A Lifelong Learning Cycle for Visual Recognition
Christoph Käding and Erik Rodner and Alexander Freytag and Joachim Denzler.
European Symposium on Artificial Neural Networks (ESANN). Pages 381-386. 2016.
[bibtex] [pdf] [code] [presentation] [abstract]

Neither Quick Nor Proper -- Evaluation of QuickProp for Learning Deep Neural Networks
Clemens-Alexander Brust and Sven Sickert and Marcel Simon and Erik Rodner and Joachim Denzler. 2016. Technical Report TR-FSU-INF-CV-2016-01
[bibtex] [pdf] [abstract]

Fine-tuning Deep Neural Networks in Continuous Learning Scenarios
Christoph Käding and Erik Rodner and Alexander Freytag and Joachim Denzler.
ACCV Workshop on Interpretation and Visualization of Deep Neural Nets (ACCV-WS). 2016.
[bibtex] [pdf] [web] [supplementary] [abstract]

Semantic Volume Segmentation with Iterative Context Integration for Bio-medical Image Stacks
Sven Sickert and Erik Rodner and Joachim Denzler.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 26 (1): pages 197-204. 2016.
[bibtex] [pdf] [abstract]

Hot spots of multivariate extreme anomalies in Earth observations
Milan Flach and Sebastian Sippel and Paul Bodesheim and Alexander Brenning and Joachim Denzler and Fabian Gans and Yanira Guanche and Markus Reichstein and Erik Rodner and Miguel D. Mahecha.
American Geophysical Union Fall Meeting (AGU): Abstract + Oral Presentation. 2016.
[bibtex] [web] [abstract]

Convolutional Neural Networks as a Computational Model for the Underlying Processes of Aesthetics Perception
Joachim Denzler and Erik Rodner and Marcel Simon.
ECCV Workshop on Computer Vision for Art Analysis. 2016.
[bibtex] [pdf] [web]

Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of Convolutional Neural Networks Approaches
Erik Rodner and Marcel Simon and Bob Fisher and Joachim Denzler.
British Machine Vision Conference (BMVC). 2016.
[bibtex] [pdf] [supplementary]

An Automated Whisker Tracking Tool for the Rat Facial Nerve Injury Paradigm
Benjamin Dorschner and Herbert Süße and Wolfgang Ortmann and Andrey Irintchev and Joachim Denzler and Orlando Guntinas-Lichius.
Journal of Neuroscience Methods. 271: pages 143-148. 2016.
[bibtex] [web] [abstract]

Vegetation segmentation in cornfield images using bag of words
Yerania Campos and Erik Rodner and Joachim Denzler and Humberto Sossa and Gonzalo Pajares.
Advanced Concepts for Intelligent Vision Systems (Acivs). Pages 193-204. 2016.
[bibtex] [pdf] [web] [abstract]

Detecting Multivariate Biosphere Extremes
Yanira Guanche Garcia and Erik Rodner and Milan Flach and Sebastian Sippel and Miguel Mahecha and Joachim Denzler.
International Workshop on Climate Informatics (CI). Pages 9-12. 2016.
[bibtex] [web] [abstract]

Facial Paresis Index Prediction by Exploiting Active Appearance Models for Compact Discriminative Features
Luise Modersohn and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 271-278. 2016.
[bibtex] [pdf] [abstract]

Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates
Alexander Freytag and Erik Rodner and Marcel Simon and Alexander Loos and Hjalmar Kühl and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 51-63. 2016.
[bibtex] [pdf] [web] [supplementary] [abstract]

Large-scale Active Learning with Approximated Expected Model Output Changes
Christoph Käding and Alexander Freytag and Erik Rodner and Andrea Perino and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 179-191. 2016.
[bibtex] [pdf] [web] [code] [supplementary] [abstract]

Lifelong Learning for Visual Recognition Systems
Alexander Freytag. 2016. ISBN 9783843929950
[bibtex] [pdf] [web]

Multilayer Markov Random Field models for change detection in optical remote sensing images
Csaba Benedek and Maha Shadaydeh and Zoltan Kato and Tamas Sziranyi and Josiane Zerubia.
ISPRS Journal of Photogrammetry and Remote Sensing. 107: pages 22-37. 2015.
[bibtex] [pdf] [web] [abstract]

Fahrbahnzustandserkennung als grundlegender Baustein für das Umfeldmodell
Bernd Hartmann and Manuel Amthor and Waldemar Jarisa.
VDI-Fachkonferenz - Innovative Bremstechnik. 2015.
[bibtex] [abstract]

Abstract: Der Wunsch, den Fahrbahnzustand oder gar den zwischen Reifen und Fahrbahn zur Verfügung stehenden Reibbeiwert vorausschauend, robust und möglichst präzise zu erfassen, ist nicht neu und beschäftigt seit mehreren Jahrzehnten aber spätestens seit dem EUREKA-Prometheus-Projekt (PROgraMme for a European Traffic of Highest Efficiency and Unprecedented Safety, 19861994) die weltweite Automobil- und Zulieferindustrie. Das Haftungspotenzial zwischen Reifen und Fahrbahn bestimmt die physikalischen Grenzen der Fahrdynamik und ist somit ausschlaggebender Faktor für die aktive Sicherheit von Kraftfahrzeugen. Erfreulicherweise haben sich die Rahmenbedingungen zur Entwicklung solcher Systeme in den letzten Jahren stark zum Positiven verändert. Einerseits steigt der Vernetzungsgrad der Fahrzeuge stetig und die Sensorentwicklung macht gerade im Bereich der Umfeldsensorik große Fortschritte. Die Evolution der Fahrdynamik- und Fahrerassistenzsysteme fordert neben einer deutlich steigenden Rechenleistung für Integrationsplattformen immer genauere und teilweise auch redundante Umfeldsensoren bei gleichzeitig größeren Erfassungsbereichen für das Sensor-Setup. Andererseits ergeben sich gerade durch die Fahrerassistenz neue Anwendungsfälle, die schon bei reduzierten Anforderungen funktional einen Mehrwert durch Einbeziehung von Informationen zum Fahrbahnzustand versprechen. Der hier beschriebene Ansatz zielt darauf ab, über die Fusion bereits existierender Fahrzeugsensoren, wie beispielsweise Wetter-, Inertial- und Umfeldsensorik ergänzt um digitale Wetterkarten und Backendinformationen, den Fahrbahnzustand zu bestimmen und daraus eine Reibwertklasse abzuleiten, die nutzbringend für die Adaption von Fahrerassistenzsystemen genutzt werden kann. Wo die Kenntnis des Fahrbahnzustands für manuelles, assistiertes oder teilautomatisiertes Fahren noch einen nützlichen funktionalen Mehrwert verspricht, ist sie für Systeme des Hoch- und Vollautomatisierten Fahrens eine zwingende Voraussetzung.

Finding Demand for Products in the Social Web
Philipp Berger and Patrick Hennig and Stefan Bunk and Dimitri Korsch and Daniel Kurzynski and Christoph Meinel.
IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity). Pages 432-439. 2015.
[bibtex]

Fine-grained Recognition Datasets for Biodiversity Analysis
Erik Rodner and Marcel Simon and Gunnar Brehm and Stephanie Pietsch and J. Wolfgang Wägele and Joachim Denzler.
CVPR Workshop on Fine-grained Visual Classification (CVPR-WS). 2015.
[bibtex] [pdf] [web]

Automated analysis of confocal laser endomicroscopy images to detect head and neck cancer
Andreas Dittberner and Erik Rodner and Wolfgang Ortmann and Joachim Stadler and Carsten Schmidt and Iver Petersen and Andreas Stallmach and Joachim Denzler and Orlando Guntinas-Lichius.
Head \& Neck. 38 (1): 2015.
[bibtex] [web]

Ranking drivers of global carbon and energy fluxes over land
Gustau Camps-Valls and Martin Jung and Kazuhito Ichii and Dario Papale and Gianluca Tramontana and Paul Bodesheim and Christopher Schwalm and Jakob Zscheischler and Miguel D. Mahecha and Markus Reichstein.
IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Pages 4416-4419. 2015.
[bibtex] [pdf] [web] [abstract]

Analysis and Classification of Microscopy Images with Cell Border Distance Statistics
Erik Rodner and Wolfgang Ortmann and Andreas Dittberner and Joachim Stadler and Carsten Schmidt and Iver Petersen and Andreas Stallmach and Joachim Denzler and Orlando Guntinas-Lichius.
Jahrestagung der Deutschen Gesellschaft für Medizinische Physik (DGMP). 2015.
[bibtex] [pdf]

Beyond Thinking in Common Categories: Predicting Obstacle Vulnerability using Large Random Codebooks
Johannes Rühle and Erik Rodner and Joachim Denzler.
Machine Vision Applications (MVA). Pages 198-201. 2015.
[bibtex] [pdf] [web] [abstract]

An improved mutual information similarity measure for registration of multi-modal remote sensing images
Maha Shadaydeh and Tamas Sziranyi.
Proc. SPIE Remote Sensing. 9643: pages 9643 - 9643 - 7. 2015.
[bibtex] [web] [abstract]

Understanding Object Descriptions in Robotics by Open-vocabulary Object Retrieval and Detection
Sergio Guadarrama and Erik Rodner and Kate Saenko and Trevor Darrell.
International Journal of Robotics Research (IJRR). 35 (1-3): pages 265-280. 2015.
[bibtex] [pdf] [web]

Novel computer vision algorithm for the reliable analysis of organelle morphology in whole cell 3D images - a pilot study for the quantitative evaluation of mitochondrial fragmentation in amyotrophic lateral sclerosis
Janin Lautenschläger and Christian Lautenschläger and Vedrana Tadic and Herbert Süße and Wolfgang Ortmann and Joachim Denzler and Andreas Stallmach and Otto W. Witte and Julian Grosskreutz.
Mitochondrion. 25 (1): pages 49-59. 2015.
[bibtex] [web]

Efficient Convolutional Patch Networks for Scene Understanding
Clemens-Alexander Brust and Sven Sickert and Marcel Simon and Erik Rodner and Joachim Denzler.
CVPR Workshop on Scene Understanding (CVPR-WS). 2015. Poster presentation and extended abstract
[bibtex] [pdf] [abstract]

Automated and objective action coding of facial expressions in patients with acute facial palsy
Daniel Haase and Laura Minnigerode and Gerd F. Volk and Joachim Denzler and Orlando Guntinas-Lichius.
European Archives of Oto-Rhino-Laryngology. 272 (5): pages 1259-1267. 2015.
[bibtex] [web] [abstract]

Regularized Geometric Hulls for Bio-medical Image Segmentation
Marco Körner and Mahesh Venkata Krishna and Herbert Süße and Wolfgang Ortmann and Joachim Denzler.
Annals of the BMVA. pages 1-12. 2015.
[bibtex] [pdf] [abstract]

Interactive Image Retrieval for Biodiversity Research
Alexander Freytag and Alena Schadt and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 129-141. 2015.
[bibtex] [pdf] [abstract]

Road Condition Estimation based on Spatio-Temporal Reflection Models
Manuel Amthor and Bernd Hartmann and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 3-15. 2015.
[bibtex] [pdf] [abstract]

Neural Activation Constellations: Unsupervised Part Model Discovery with Convolutional Networks
Marcel Simon and Erik Rodner.
International Conference on Computer Vision (ICCV). Pages 1143-1151. 2015.
[bibtex] [pdf] [web] [abstract]

Change Detection in Wetlands using Multi-layer Fusion Markov Random Field
Maha Shadaydeh and Andrea Manno-Kovacs and Tamas Sziranyi.
What can Remote Sensing do for the Conservation of Wetlands? - 1st International Symposium. 2015.
[bibtex]

Fine-grained Classification of Identity Document Types with Only One Example
Marcel Simon and Erik Rodner and Joachim Denzler.
Machine Vision Applications (MVA). Pages 126-129. 2015.
[bibtex] [pdf] [web] [abstract]

Convolutional Patch Networks with Spatial Prior for Road Detection and Urban Scene Understanding
Clemens-Alexander Brust and Sven Sickert and Marcel Simon and Erik Rodner and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 510-517. 2015.
[bibtex] [pdf] [abstract]

Active Learning and Discovery of Object Categories in the Presence of Unnameable Instances
Christoph Käding and Alexander Freytag and Erik Rodner and Paul Bodesheim and Joachim Denzler.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pages 4343-4352. 2015.
[bibtex] [pdf] [web] [code] [presentation] [supplementary] [abstract]

Local Novelty Detection in Multi-class Recognition Problems
Paul Bodesheim and Alexander Freytag and Erik Rodner and Joachim Denzler.
IEEE Winter Conference on Applications of Computer Vision (WACV). Pages 813-820. 2015.
[bibtex] [pdf] [web] [supplementary] [abstract]

Mixed Gaits in Small Avian Terrestrial Locomotion
Emanuel Andrada and Daniel Haase and Yefta Sutedja and John A. Nyakatura and Brandon M. Kilbourne and Joachim Denzler and Martin S. Fischer and Reinhard Blickhan.
Scientific Reports. 5: 2015.
[bibtex] [web] [abstract]

Croatian Fish Dataset: Fine-grained classification of fish species in their natural habitat
Jonas Jäger and Marcel Simon and Joachim Denzler and Viviane Wolff and Klaus Fricke-Neuderth and Claudia Kruschel.
BMVC Workshop on Machine Vision of Animals and their Behaviour (BMVC-WS). 2015.
[bibtex] [pdf] [web]

Additional Traffic Sign Detection: A Comparative Study
Thomas Wenzel and Steffen Brueggert and Joachim Denzler.
IEEE International Conference on Intelligent Transportation Systems (ITSC). Pages 794-799. 2015.
[bibtex] [pdf] [abstract]

Selecting Influential Examples: Active Learning with Expected Model Output Changes
Alexander Freytag and Erik Rodner and Joachim Denzler.
European Conference on Computer Vision (ECCV). Pages 562-577. 2014.
[bibtex] [pdf] [presentation] [supplementary] [abstract]

Superpixel-gestützte Klassifikation von Stechmücken mit der Bag-of-Features-Methode
Paul Grigoriev and Jonas Jäger and Viviane Wolff and Klaus Fricke-Neuderth.
Forum Bildverarbeitung 2014. Pages 191-202. 2014.
[bibtex] [web]

A Combination of Generative and Discriminative Models for Fast Unsupervised Activity Recognition from Traffic Scene Videos
Mahesh Venkata Krishna and Joachim Denzler.
IEEE Winter Conference on Applications of Computer Vision (WACV). Pages 640-645. 2014.
[bibtex] [pdf] [web] [abstract]

ERNA - Embedded, Self-Calibrating Robotic-Arm for Gamificated Learning
Carsten Seeger and Christoph Käding and Christopher Manthey and David Neuhäuser.
Communications, Circuits and Educational Technologies, International Conference on Education and Educational Technologies II (ECS-EET). Pages 19-24. 2014.
[bibtex]

A methodology for deriving extreme nearshore sea conditions for structural design and flood risk analysis
Ben Gouldby and Fernando J. Mendez and Yanira Guanche and Ana Rueda and Roberto Minguez.
Coastal Engineering. pages 15-26. 2014.
[bibtex] [abstract]

Instance-weighted Transfer Learning of Active Appearance Models
Daniel Haase and Erik Rodner and Joachim Denzler.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pages 1426-1433. 2014.
[bibtex] [pdf] [abstract]

Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature extraction methods
Alexander Freytag and Johannes Rühle and Paul Bodesheim and Erik Rodner and Joachim Denzler. 2014. Technical Report TR-FSU-INF-CV-2014-01
[bibtex] [pdf] [code] [abstract]

Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature extraction methods
Alexander Freytag and Johannes Rühle and Paul Bodesheim and Erik Rodner and Joachim Denzler.
ICPR Workshop on Features and Structures (FEAST): Extended Abstract + Poster Presentation. 2014. Best Poster Award
[bibtex] [pdf] [code] [presentation]

An Improved Variant of the Conventional Harmony Search Algorithm
Jhonatan Contreras and Ivan Amaya and Rodrigo Correa.
Applied Mathematics and Computation. 227 (1): pages 821-830. 2014.
[bibtex] [web] [abstract]

Semantic Volume Segmentation with Iterative Context Integration
Sven Sickert and Erik Rodner and Joachim Denzler.
Open German-Russian Workshop on Pattern Recognition and Image Understanding (OGRW). Pages 220-225. 2014.
[bibtex] [pdf] [web] [abstract]

Exemplar-specific Patch Features for Fine-grained Recognition
Alexander Freytag and Erik Rodner and Trevor Darrell and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 144-156. 2014.
[bibtex] [pdf] [code] [supplementary] [abstract]

An improved local similarity measure estimation for change detection in remote sensing images
Maha Shadaydeh and Tamas Sziranyi.
International Conference on Aerospace Electronics and Remote Sensing Technology. Pages 234-238. 2014.
[bibtex] [web] [abstract]

Asymmetric and Category Invariant Feature Transformations for Domain Adaptation
Judy Hoffman and Erik Rodner and Jeff Donahue and Brian Kulis and Kate Saenko.
International Journal of Computer Vision (IJCV). 109 (1-2): pages 28-41. 2014.
[bibtex] [pdf] [web] [abstract]

A method for finding the optimal predictor indices for local wave climate conditions
Paula Camus and Fernando J. Mendez and Inigo J. Losada and Melisa Menendez and Antonio Espejo and Jorge Perez and Ana Rueda and Yanira Guanche.
Ocean Dynamics. pages 1025-1038. 2014.
[bibtex] [abstract]

Bildverarbeitung und Objekterkennung: Computer Vision in Industrie und Medizin
Herbert Süße and Erik Rodner. 2014. Neues umfangreiches Lehrbuch im Bereich Bildverarbeitung und maschinelles Lernen
[bibtex] [web] [abstract]

Robust Pictorial Structures for X-ray Animal Skeleton Tracking
Manuel Amthor and Daniel Haase and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 351-359. 2014.
[bibtex] [pdf] [abstract]

Open-vocabulary Object Retrieval
Sergio Guadarrama and Erik Rodner and Kate Saenko and Ning Zhang and Ryan Farrell and Jeff Donahue and Trevor Darrell.
Robotics Science and Systems (RSS). Pages 41, ISBN 978-0-9923747-0-9. 2014. Awarded with an AAAI invited talk
[bibtex] [pdf] [web] [abstract]

A Graph-based MAP Solution for Multi-Person Tracking Using Multi-Camera Systems
Xiaoyan Jiang and Marco Körner and Daniel Haase and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 343-350. 2014.
[bibtex] [web]

Segmentation of Remote Sensing Images Using Similarity-Measure-Based Fusion-MRF Model
Tamas Sziranyi and Maha Shadaydeh.
IEEE Geoscience and Remote Sensing Letters. 11 (9): pages 1544-1548. 2014.
[bibtex] [pdf] [web] [abstract]

Vulnerability Classification of Generic Object Hypotheses using a Visual Words Approach
Johannes Rühle and Maxim Arbitmann and Joachim Denzler.
FISITA World Automotive Congress (FISITA). Pages 1-5. 2014. F2014-AST-045
[bibtex] [abstract]

Nonparametric Part Transfer for Fine-grained Recognition
Christoph Göring and Erik Rodner and Alexander Freytag and Joachim Denzler.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pages 2489-2496. 2014.
[bibtex] [pdf] [web] [code] [presentation] [abstract]

Closure of discussion: Point-in-time and extreme-value probability simulation technique for engineering design
Roberto Minguez and Yanira Guanche and Fernando J. Mendez.
Structural Safety. pages 5-7. 2014.
[bibtex] [abstract]

Explorative Analysis of Heterogeneous, Unstructured, and Uncertain Data: A Computer Science Perspective on Biodiversity Research
C. Beckstein and S. Böcker and M. Bogdan and H. Bruelheide, H. M. Bücker and Joachim Denzler and P. Dittrich and I. Grosse and A. Hinneburg and B. König-Ries and F. Löffler and M. Marz and M. Müller-Hannemann and M. Winter and W. Zimmermann.
International Conference on Data Management Technologies and Applications (DATA). Pages 251-257. 2014.
[bibtex] [abstract]

Birds of a Feather Flock Together - Local Learning of Mid-level Representations for Fine-grained Recognition
Alexander Freytag and Erik Rodner and Joachim Denzler.
ECCV Workshop on Parts and Attributes (ECCV-WS). 2014.
[bibtex] [pdf] [web] [code] [presentation]

JenAesthetics Subjective Dataset: Analyzing Paintings by Subjective Scores
Seyed Ali Amirshahi and Gregor Uwe Hayn-Leichsenring and Joachim Denzler and Christoph Redies.
ECCV Workshop on Computer Vision for Art Analysis (ECCV-WS). 2014.
[bibtex]

ARTOS -- Adaptive Real-Time Object Detection System
Björn Barz and Erik Rodner and Joachim Denzler.
arXiv preprint arXiv:1407.2721. 2014.
[bibtex] [pdf] [web] [code] [abstract]

Intrinsic and extrinsic active self-calibration of multi-camera systems
Marcel Brückner and Ferid Bajramovic and Joachim Denzler.
Mach. Vis. Appl.. 25 (2): pages 389-403. 2014.
[bibtex] [web]

A Hierarchical Bayesian Approach for Unsupervised Cell Phenotype Clustering
Mahesh Venkata Krishna and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 69-80. 2014.
[bibtex] [pdf] [abstract]

Evaluating the rule of thirds in photographs and paintings
Seyed Ali Amirshahi and Gregor Uwe Hayn-Leichsenring and Joachim Denzler and Christoph Redies.
Art and Perception. 2014.
[bibtex]

Regularized Geometric Hulls for Robust Cell Nucleus Segmentation from Microscopy Images
Marco Körner and Mahesh Venkata Krishna and Herbert Süße and Wolfgang Ortmann and Joachim Denzler.
Conference in Medical Image Understanding and Analysis (MIUA). Pages 117-122. 2014.
[bibtex] [pdf]

Zweistufige Anwendung der Saliency-Methodik zur Stechmückendetektion
Jonas Jäger and Viviane Wolff and Klaus Fricke-Neuderth.
Forum Bildverarbeitung 2014. Pages 203-214. 2014.
[bibtex] [web]

Temporal Video Segmentation by Event Detection: A Novelty Detection Approach
Mahesh Venkata Krishna and Paul Bodesheim and Marco Körner and Joachim Denzler.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 24 (2): pages 243-255. 2014.
[bibtex] [pdf] [web] [abstract]

Comparative Large-Scale Evaluation of Human and Active Appearance Model Based Tracking Performance of Anatomical Landmarks in X-ray Locomotion Sequences
Daniel Haase and John A. Nyakatura and Joachim Denzler.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 24 (1): pages 86-92. 2014.
[bibtex] [web] [abstract]

Part Localization by Exploiting Deep Convolutional Networks
Marcel Simon and Erik Rodner and Joachim Denzler.
ECCV Workshop on Parts and Attributes (ECCV-WS). 2014.
[bibtex] [pdf] [web]

Part Detector Discovery in Deep Convolutional Neural Networks
Marcel Simon and Erik Rodner and Joachim Denzler.
Asian Conference on Computer Vision (ACCV). Pages 162-177. 2014.
[bibtex] [pdf] [code] [abstract]

Interactive Adaptation of Real-Time Object Detectors
Daniel Göhring and Judy Hoffman and Erik Rodner and Kate Saenko and Trevor Darrell.
International Conference on Robotics and Automation (ICRA). Pages 1282-1289. 2014.
[bibtex] [pdf] [web] [abstract]

An ensemble of global high-resolution products of energy fluxes over land
Martin Jung and Kazuhito Ichii and Gustau Camps-Valls and Dario Papale and Gianluca Tramontana and Sven Sickert and Christopher Schwalm and Markus Reichstein.
International Scientific Conference on the Global Water and Energy Cycle (GEWEX). 2014. Poster
[bibtex] [abstract]

Detection of Object Interactions in Video Sequences
Ali Al-Raziqi and Mahesh Venkata Krishna and Joachim Denzler.
Open German-Russian Workshop on Pattern Recognition and Image Understanding (OGRW). Pages 156-161. 2014.
[bibtex] [pdf] [web] [abstract]

From regular text to artistic writing and artworks: Fourier statistics of images with low and high aesthetic appeal
Tamara Melmer and Seyed Ali Amirshahi and Michael Koch and Joachim Denzler and Christoph Redies.
Frontiers in Human Neuroscience. 7 (00106): 2013.
[bibtex] [abstract]

Lighting estimation in fringe images during motion compensation for 3D measurements
Andreas Breitbarth and Peter Kühmstedt and Gunther Notni and Joachim Denzler.
Videometrics, Range Imaging, and Applications XII; and Automated Visual Inspection. Pages 87910P:1-9. 2013.
[bibtex] [pdf] [web] [abstract]

Abstract: Fringe projection is an established method to measure the 3D structure of macroscopic objects. To receive both a high accuracy and robustness a certain number of images with pairwise different projection pattern is necessary. Over this sequence it is necessary that each 3D object point corresponds to the same image point at every time. This situation is no longer given for moving measurement objects. One possibility to solve this problem is to restore the static situation. Therefore, the acquired camera images have to be realigned and secondly the degree of fringe shift hast to be estimated. Furthermore, there exists another variable: change in lighting. These variances cannot be compensated, but it has to be approximately determined and integrated into the calculation process of 3D data. The possibility to obtain an accurate measurement is not being given because due to the condition that each arbitrary interferogram comprised three unknowns: additive and multiplicative intensity distortion and the phase distribution. The changes in lighting are described by the first two parameters and have to be determined for each camera pixel and each image. So, there is a trade-off problem: Two variables, but only one equation. We propose a method to estimate these lighting changes for each camera pixel with respect to their neighbors at each point in time. The size of local neighborhoods in the presented algorithms is chosen adaptively in respect to the gradients of object structure because for accurate 3D measurements you need both: sharp edges and on the other side smoothness in regions with very low contrast in intensities or wide fringe periods. To speed up the estimation of lighting values, not all pixel of the neighborhood were taken into account. Depending on the direction of projected fringes, either axially parallel or diagonal adjacent pixels are used. Taken together, our method results in a motion compensated dense 3D point cloud without any artifacts.

Component-based Pedestrian Recognition for Advanced Driver Assistance Systems
Martin Rapus. 2013.
[bibtex]

Autoregressive logistic regression applied to atmospheric circulation patterns
Yanira Guanche and Roberto Minguez and Fernando J. Mendez.
Climate Dynamics. 42 (1): pages 537-552. 2013.
[bibtex] [abstract]

Automated Approximation of Center of Mass Position in X-ray Sequences of Animal Locomotion
Daniel Haase and Emanuel Andrada and John A. Nyakatura and Brandon M. Kilbourne and Joachim Denzler.
Journal of Biomechanics. 46 (12): pages 2082-2086. 2013.
[bibtex]

A simplified method to downscale wave dynamics on vertical breakwaters
Yanira Guanche and Paula Camus and Raul Guanche and Fernando J. Mendez and Raul Medina.
Coastal Engineering. 71: pages 68-77. 2013.
[bibtex] [abstract]

Abstract: A coastal structure is usually designed with the final objective to guarantee its functionality and stability throughout its life cycle. Regarding stability, the three main failure modes are sliding, overturning and failure of the foundations. To accomplish the design objectives, a design sea state is usually used when calculating the loads and scour around the structure. This design sea state corresponds to a certain sea state with specific return period values of a significant wave height. However, the combination of different simultaneous sea state parameters can produce other critical situations compromising the stability of the structure which then require the calculation of long time series of wave forces corresponding to long-term historical wave situations. Moreover, a design force associated to a certain return period can be defined from the time series of the stability parameters. The most accurate techniques which can be used to estimate structure stability are based on numerical and physical models, but these are very time consuming and the calculation of long time series is therefore unfeasible. Here, we propose a hybrid methodology to transform wave conditions into wave forces acting upon vertical structures and scour around it. The methodology consists of a selection of a subset of sea states representative of wave climate at the structure location, using a maximum dissimilarity algorithm, The wave forces acting upon the structure and scour around it, for the wave situations selected, are then estimated as is the reconstruction of the calculated parameters corresponding to historical sea states using an interpolation technique based on radial basis function. The validation of the results, through a direct comparison between reconstructed series and analytically (semi-empirical formulations) calculated ones, confirms the ability of the developed methodology to reconstruct time series of stability parameters on vertical breakwaters. This methodology allows its application to numerical and physical models.

Color: A Crucial Factor for Aesthetic Quality Assessment in a Subjective Database of Paintings
Seyed Ali Amirshahi and Gregor Uwe Hayn-Leichsenring and Joachim Denzler and Christoph Redies.
Congress of the International Colour Association (AIC). 2013.
[bibtex]

Towards Adapting ImageNet to Reality: Scalable Domain Adaptation with Implicit Low-rank Transformations
Erik Rodner and Judy Hoffman and Jeff Donahue and Trevor Darrell and Kate Saenko.
arXiv preprint arXiv:1308.4200. 2013.
[bibtex] [pdf]

Landbedeckungsklassifikation von Satellitenaufnahmen unter Verwendung von Kontextinformation mit minimaler menschlicher Interaktion
Eric Bach and Björn Fröhlich and Irene Walde and Sören Hese and Christiane Schmullius and Joachim Denzler.
Band 22 der Jahrestagung der Deutschen Gesellschaft für Photogrammetrie. 2013.
[bibtex] [pdf]

Point-in-time and extreme-value probability simulation technique for engineering design
Roberto Minguez and Yanira Guanche and Fernando J. Mendez.
Structural Safety. 41: pages 29-36. 2013.
[bibtex] [abstract]

2D and 3D Analysis of Animal Locomotion from Biplanar X-ray Videos Using Augmented Active Appearance Models
Daniel Haase and Joachim Denzler.
EURASIP Journal on Image and Video Processing. 45: pages 1-13. 2013.
[bibtex] [pdf]

I Want To Know More: Efficient Multi-Class Incremental Learning Using Gaussian Processes
Alexander Lütz and Erik Rodner and Joachim Denzler.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 23 (3): pages 402-407. 2013.
[bibtex] [pdf]

How self-similar are artworks at different levels of spatial resolution?
Seyed Ali Amirshahi and Christoph Redies and Joachim Denzler.
Computational Aesthetics. 2013.
[bibtex]

Climate-based Monte Carlo simulation of trivariate sea states
Yanira Guanche and Roberto Minguez and Fernando J. Mendez.
Coastal Engineering. 80: pages 107-121. 2013.
[bibtex] [abstract]

Efficient Measuring of Facial Action Unit Activation Intensities using Active Appearance Models
Daniel Haase and Michael Kemmler and Orlando Guntinas-Lichius and Joachim Denzler.
Machine Vision Applications (MVA). Pages 141-144. 2013.
[bibtex] [pdf]

Automated Classification of Therapeutic Face Exercises using the Kinect.
Cornelia Lanz and Birant Sibel Olgay and Joachim Denzler and Horst-Michael Gross.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 556-565. 2013. Best Paper Award
[bibtex]

Transform-based Domain Adaptation for Big Data
Erik Rodner and Judy Hoffman and Jeff Donahue and Trevor Darrell and Kate Saenko.
NIPS Workshop on New Directions in Transfer and Multi-Task Learning (NIPS-WS). 2013. abstract version of arXiv:1308.4200
[bibtex] [pdf] [abstract]

Improved segmentation of a series of remote sensing images by using a fusion MRF model
Tamas Sziranyi and Maha Shadaydeh.
International Workshop on Content-Based Multimedia Indexing (CBMI). Pages 137-142. 2013.
[bibtex] [web] [abstract]

Implementation of a Secure and Reliable Storage Above the Untrusted Clouds
Maxim Schnjakin and Dimitri Korsch and Martin Schoenberg and Christoph Meinel.
International Conference on Computer Science \& Education (ICCSE). Pages 347-353. 2013.
[bibtex]

Oriented Differences of Boxes Operators for Blood Vessel Segmentation and Analysis in Confocal Laser Endomicroscopy Images with minimal User Interaction
Herbert Süße and Wolfgang Ortmann and Christian Lautenschläger and Marco Körner and Carsten Schmidt and Andreas Stallmach and Joachim Denzler.
Annual Conference in Medical Image Understanding and Analysis (MIUA). Pages 155-160. 2013.
[bibtex] [pdf]

Kernel Null Space Methods for Novelty Detection
Paul Bodesheim and Alexander Freytag and Erik Rodner and Michael Kemmler and Joachim Denzler.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pages 3374-3381. 2013.
[bibtex] [pdf] [web] [code] [presentation] [abstract]

Large-Scale Gaussian Process Multi-Class Classification for Semantic Segmentation and Facade Recognition
Björn Fröhlich and Erik Rodner and Michael Kemmler and Joachim Denzler.
Machine Vision and Applications. 24 (5): pages 1043-1053. 2013.
[bibtex] [pdf]

Efficient Learning of Domain-invariant Image Representations
Judy Hoffman and Erik Rodner and Jeff Donahue and Trevor Darrell and Kate Saenko.
International Conference on Learning Representations (ICLR). 2013.
[bibtex] [pdf]

JAR-Aibo: A Multi-View Dataset for Evaluation of Model-Free Action Recognition Systems
Marco Körner and Joachim Denzler.
New Trends in Image Analysis and Processing ICIAP 2013. Pages 527-535. 2013.
[bibtex] [pdf]

Segmentation of Microorganism in Complex Environments
Michael Kemmler and Björn Fröhlich and Erik Rodner and Joachim Denzler.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 23 (4): pages 512-517. 2013.
[bibtex] [pdf]

Enhanced Anomaly Detection in Wire Ropes by Combining Structure and Appearance
Esther-Sabrina Wacker and Joachim Denzler.
Pattern Recognition Letters. 34 (8): pages 942-953. 2013.
[bibtex] [pdf]

Fine-grained Categorization - Short Summary of our Entry for the ImageNet Challenge 2012
Christoph Göring and Alexander Freytag and Erik Rodner and Joachim Denzler.
arXiv preprint arXiv:1310.4759. 2013.
[bibtex] [pdf] [web]

Land cover classification of satellite images using contextual information
Björn Fröhlich and Eric Bach and Irene Walde and Sören Hese and Christiane Schmullius and Joachim Denzler.
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Pages 1-6. 2013.
[bibtex] [pdf]

Hierarchical Dirichlet Processes for unsupervised online multi-view action perception using Temporal Self-Similarity features
Mahesh Venkata Krishna and Marco Körner and Joachim Denzler.
Seventh International Conference on Distributed Smart Cameras (ICDSC). Pages 1-6. 2013.
[bibtex] [pdf] [web] [abstract]

Accurate 3D Multi-Marker Tracking in X-ray Cardiac Sequences Using a Two-Stage Graph Modeling Approach
Xiaoyan Jiang and Daniel Haase and Marco Körner and Wolfgang Bothe and Joachim Denzler.
Computer Analysis of Images and Patterns. Pages 117-125. 2013.
[bibtex] [pdf]

Video Segmentation by Event Detection: A Novel One-class Classification Approach
Mahesh Venkata Krishna and Paul Bodesheim and Joachim Denzler.
4th International Workshop on Image Mining. Theory and Applications (IMTA-4). 2013.
[bibtex] [pdf] [abstract]

Mo1635 Development of an Innovative Algorithm for an Advanced Analysis of Vascular Structures: a Pilot Study Using Confocal LASER Endomicroscopy in Patients With Acute Portal Vein Thrombosis, Severe Sepsis and Healthy Controls
Carsten Schmidt and Christian Lautenschläger and Herbert Süße and Joachim Denzler and Andreas Stallmach.
Gastrointestinal Endoscopy. 77 (5): pages AB453. 2013.
[bibtex] [web]

Scalable Transform-based Domain Adaptation
Erik Rodner and Judy Hoffman and Jeff Donahue and Trevor Darrell and Kate Saenko.
ICCV Workshop on Visual Domain Adaptation (ICCV-WS). 2013.
[bibtex] [pdf]

Temporal Self-Similarity for Appearance-Based Action Recognition in Multi-View Setups
Marco Körner and Joachim Denzler.
Computer Analysis of Images and Patterns. Pages 163-171. 2013.
[bibtex] [pdf]

An Efficient Approximation for Gaussian Process Regression
Paul Bodesheim and Alexander Freytag and Erik Rodner and Joachim Denzler. 2013. Technical Report TR-FSU-INF-CV-2013-01
[bibtex] [pdf]

Labeling examples that matter: Relevance-Based Active Learning with Gaussian Processes
Alexander Freytag and Erik Rodner and Paul Bodesheim and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 282-291. 2013.
[bibtex] [pdf] [web] [code] [supplementary] [abstract]

Approximations of Gaussian Process Uncertainties for Visual Recognition Problems
Paul Bodesheim and Alexander Freytag and Erik Rodner and Joachim Denzler.
Scandinavian Conference on Image Analysis (SCIA). Pages 182-194. 2013.
[bibtex] [pdf] [web] [abstract]

Statistical image properties of print advertisements, visual artworks and images of architecture
Julia Braun and Seyed Ali Amirshahi and Joachim Denzler and Christoph Redies.
Frontiers in Psychology. 4: pages 808. 2013.
[bibtex]

Automatic Identification of Novel Bacteria using Raman Spectroscopy and Gaussian Processes
Michael Kemmler and Erik Rodner and Petra Rösch and Jürgen Popp and Joachim Denzler.
Analytica Chimica Acta. 794: pages 29-37. 2013.
[bibtex] [pdf] [web] [supplementary]

One-class Classification with Gaussian Processes
Michael Kemmler and Erik Rodner and Esther-Sabrina Wacker and Joachim Denzler.
Pattern Recognition. 46 (12): pages 3507-3518. 2013.
[bibtex] [pdf]

Numerical simulation of three-dimensional breaking waves on a gravel slope using a two-phase flow NavierStokes model
Pablo Higuera and Manuel Jesus and Javier L. Lara and Inigo J. Losada and Yanira Guanche and Gabriel Barajas.
Journal of Computational and Applied Mathematics. 246: pages 144-152. 2013.
[bibtex] [abstract]

JenAesthetics-a public dataset of paintings for aesthetic research
Seyed Ali Amirshahi and Joachim Denzler and Christoph Redies. 2013. Technical Report
[bibtex]

Semi-Supervised Domain Adaptation with Instance Constraints
Jeff Donahue and Judy Hoffman and Erik Rodner and Kate Saenko and Trevor Darrell.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pages 668 - 675. 2013.
[bibtex] [pdf]

Large-Scale Gaussian Process Classification using Random Decision Forests
Björn Fröhlich and Erik Rodner and Michael Kemmler and Joachim Denzler.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 22 (1): pages 113-120. 2012.
[bibtex] [pdf]

Motion compensation for three-dimensional measurements of macroscopic objects using fringe projection
Andreas Breitbarth and Peter Kühmstedt and Gunther Notni and Joachim Denzler.
Videometrics, Range Imaging, and Applications XII; and Automated Visual Inspection. 2012.
[bibtex] [pdf]

Universal Eye-tracking Based Text Cursor Warping
Ralf Biedert and Andreas Dengel and Christoph Käding.
Symposium on Eye Tracking Research and Applications (ETRA). Pages 361-364. 2012.
[bibtex]

Multi-Person Tracking-by-Detection based on Calibrated Multi-Camera Systems
Xiaoyan Jiang and Erik Rodner and Joachim Denzler.
International Conference on Computer Vision and Graphics. Pages 743-751. 2012.
[bibtex] [pdf]

PHOG-Derived Aesthetic Measures Applied to Color Photographs of Artworks, Natural Scenes and Objects
Christoph Redies and Seyed Ali Amirshahi and Michael Koch and Joachim Denzler.
European Conference on Computer Vision (ECCV) VISART workshop. 2012.
[bibtex]

Finding Discriminative Features for Raman Spectroscopy
Michael Kemmler and Joachim Denzler.
International Conference on Pattern Recognition. Pages 1823-1826. 2012.
[bibtex] [pdf]

Rapid Uncertainty Computation with Gaussian Processes and Histogram Intersection Kernels
Alexander Freytag and Erik Rodner and Paul Bodesheim and Joachim Denzler.
Asian Conference on Computer Vision (ACCV). Pages 511-524. 2012. Best Paper Honorable Mention Award
[bibtex] [pdf] [web] [presentation] [abstract]

Semantic Segmentation with Millions of Features: Integrating Multiple Cues in a Combined Random Forest Approach
Björn Fröhlich and Erik Rodner and Joachim Denzler.
Asian Conference on Computer Vision (ACCV). Pages 218-231. 2012.
[bibtex] [pdf]

Lernen mit wenigen Beispielen für die visuelle Objekterkennung
Erik Rodner.
Ausgezeichnete Informatikdissertationen 2011. 2012. in german
[bibtex] [pdf] [web]

Analyzing the Subspaces Obtained by Dimensionality Reduction for Human Action Recognition from 3d Data
Marco Körner and Joachim Denzler.
IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS). Pages 130-135. 2012.
[bibtex] [pdf]

Divergence-Based One-Class Classification Using Gaussian Processes
Paul Bodesheim and Erik Rodner and Alexander Freytag and Joachim Denzler.
British Machine Vision Conference (BMVC). Pages 50.1-50.11. 2012.
[bibtex] [pdf] [web] [presentation] [abstract]

Large-Scale Gaussian Process Classification with Flexible Adaptive Histogram Kernels
Erik Rodner and Alexander Freytag and Paul Bodesheim and Joachim Denzler.
European Conference on Computer Vision (ECCV). Pages 85-98. 2012.
[bibtex] [pdf] [web] [supplementary] [abstract]

Human Optic Sensitivity Computation Based on Singular Value Decomposition
Seyed Ali Amirshahi and Farah Torkamani-Azar.
Optica Applicata. 42 (1): 2012.
[bibtex]

Entwicklung eines neuen Gefäßdetektionsalgorithmus unter Verwendung der konfokale Laserendoskopie zur Erfassung der mukosalen Mikrozirkulation: Eine Pilotstudie an Patienten mit akuter Pfortaderthrombose, schwerer Sepsis und gesunden Kontrollen
Carsten Schmidt and Christian Lautenschläger and Herbert Süsse and Joachim Denzler and Andreas Stallmach.
Zeitschrift für Gastroenterologie. 50 (8): pages 277. 2012.
[bibtex] [web]

As Time Goes By: Anytime Semantic Segmentation with Iterative Context Forests
Björn Fröhlich and Erik Rodner and Joachim Denzler.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 1-10. 2012.
[bibtex] [pdf]

Visualization of Barium Titanate Phase Transition using Quantization of Dipole Moment Vectors
Henry Lehmann and Patrick Heyne and Oliver Mothes and Heiko Müller and Tim Smyth and Erik Berger and Katja Fiedler and David Vogt and Bernhard Jung.
Electronic Proceedings IEEE VisWeek. 2012. Third Place Award IEEE SciVis Contest 2012
[bibtex] [pdf] [abstract]

PHOG Analysis of Self-Similarity in Aesthetic Images
Seyed Ali Amirshahi and Michael Koch and Joachim Denzler and Christoph Redies.
Human Vision and Electronic Imaging XVII. 2012.
[bibtex]

Beyond Classification - Large-scale Gaussian Process Inference and Uncertainty Prediction
Alexander Freytag and Erik Rodner and Paul Bodesheim and Joachim Denzler.
Big Data Meets Computer Vision: First International Workshop on Large Scale Visual Recognition and Retrieval (NIPS-WS). 2012. This workshop article is a short version of our ACCV 2012 paper.
[bibtex] [pdf] [abstract]

Fast and Robust Landmark Tracking in X-ray Locomotion Sequences Containing Severe Occlusions
Manuel Amthor and Daniel Haase and Joachim Denzler.
International Workshop on Vision, Modelling, and Visualization (VMV). Pages 15-22. 2012.
[bibtex] [abstract]

Data Association for Multi-Object Tracking-by-Detection in Multi-Camera Networks
Michael Bredereck and Xiaoyan Jiang and Marco Körner and Joachim Denzler.
ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC). 2012.
[bibtex] [pdf]

Assessment of the Rule of Thirds in Photographs Taken by Amateurs
Seyed Ali Amirshahi and Christoph Redies and Joachim Denzler.
Visual Science of Art Conference (VSAC). 2012.
[bibtex]

Scale-Independent Spatio-Temporal Statistical Shape Representations for 3d Human Action Recognition
Marco Körner and Daniel Haase and Joachim Denzler.
International Conference on Pattern Recognition and Methods (ICPRAM). Pages 288-294. 2012.
[bibtex] [pdf]

Selection of Relevant Features for Raman Spectroscopy
Michael Kemmler and Joachim Denzler. 2012. Technical Report
[bibtex] [pdf]

Semantic Segmentation using GrabCut
Christoph Göring and Björn Fröhlich and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 597-602. 2012.
[bibtex] [pdf]

Efficient Semantic Segmentation with Gaussian Processes and Histogram Intersection Kernels
Alexander Freytag and Björn Fröhlich and Erik Rodner and Joachim Denzler.
International Conference on Pattern Recognition (ICPR). Pages 3313-3316. 2012.
[bibtex] [pdf]

Tracking and Reconstruction in a Combined Optimization Approach
Olaf Kähler and Joachim Denzler.
IEEE Transactions on Pattern Analysis and Machine Intelligence. 34: pages 387-401. 2012.
[bibtex]

A multivariate approach to estimate design loads for offshore wind turbines
Yanira Guanche and Raul Guanche and Paula Camus and Fernando J. Mendez and Raul Medina.
Wind Energy. 16 (7): pages 1091-1106. 2012.
[bibtex] [abstract]

Abstract: The design of offshore wind farms is a complex process that requires a detailed study of the oceanographic, meteorological and geotechnical conditions at the site. The structure and all structural members shall be designed in a way that they can be resistant against different kinks of loads: permanent, variable, environmental, accidental and deformations. This paper is focused on those called environmental loads. The main environmental conditions that may contribute to structural damage, operational disturbances or other failures are wind, waves, currents and sea ice. Thus, the combination of the different parameters may produce many different critical situations for the integrity of the structure, requiring the calculation of long time series corresponding to long-term historical data situations. The most accurate techniques available at the moment to estimate loads acting upon a structure are numerical and physical models; however, they are very time consuming, and the calculation of long time series of data is unfeasible. Therefore, a new hybrid methodology to select waveswindcurrent representative conditions that allow the interpolation of long time series of forces on a wind turbine is proposed. The methodology consists of a selection of a subset of representative cases of wavewindcurrent climate at the structure's location by using a maximum dissimilarity algorithm, then estimating loads acting upon the structure for the seawind states selected and the reconstruction of loads corresponding to historical data using an interpolation technique based on radial basis function. To validate the proposed methodology and because of there is no availability of long time records of loads on wind turbines, the well-known IEC 614003 has been applied to estimate the loads for the complete reanalysis time series of waves, winds and currents. The validation of the results confirms the ability of the methodology developed to reconstruct time series of forces on the structure on the basis of the previously selected cases. This methodology permits application of numerical and physical models to offshore wind farm design, considerably reducing the number of tests or simulations. Copyright 2012 John Wiley & Sons, Ltd.

Combining structure and appearance for anomaly detection in wire ropes
Esther-Sabrina Wacker and Joachim Denzler.
International Conference on Computer Analysis of Images and Patterns (CAIP). Pages 163-170. 2011.
[bibtex] [pdf] [abstract]

Self-Calibration of Camera Networks: Active and Passive Methods
Marcel Brückner and Ferid Bajramovic and Joachim Denzler. 2011.
[bibtex]

1/fp Characteristics of the Fourier power spectrum affects ERP correlates of face learning and recognition
M. Blickhan and J.M. Kaufmann and Joachim Denzler and S.R. Schweinberger and Christoph Redies.
Biological Psychology. 88 (2-3): pages 204-214. 2011.
[bibtex]

Extrinsic Self-Calibration of Time-of-Flight Cameras using a Combination of 3D and Intensity Descriptors
Jörn Schmidt and Marcel Brückner and Joachim Denzler.
International Workshop on Vision, Modelling, and Visualization (VMV). Pages 269-276. 2011.
[bibtex]

Anatomical Landmark Tracking for the Analysis of Animal Locomotion in X-ray Videos Using Active Appearance Models
Daniel Haase and Joachim Denzler.
Scandinavian Conference on Image Analysis (SCIA). Pages 604-615. 2011.
[bibtex] [pdf] [abstract]

Spectral Clustering of ROIs for Object Discovery
Paul Bodesheim.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 450-455. 2011.
[bibtex] [pdf] [web] [abstract]

A Method for Fast Composing of Images Captured from Deformed Documents by a Quadocular Scanner Setup
Marco Körner and Herbert Süße and Wolfgang Ortmann and Joachim Denzler.
Machine Vision Applications (MVA). Pages 291-294. 2011.
[bibtex] [pdf]

Learning with Few Examples for Binary and Multiclass Classification Using Regularization of Randomized Trees
Erik Rodner and Joachim Denzler.
Pattern Recognition Letters. 32 (2): pages 244-251. 2011.
[bibtex] [pdf]

Learning from Few Examples for Visual Recognition Problems
Erik Rodner. 2011.
[bibtex] [pdf] [web]

One-Class Classification for Anomaly Detection in Wire Ropes with Gaussian Processes in a Few Lines of Code
Erik Rodner and Esther-Sabrina Wacker and Michael Kemmler and Joachim Denzler.
Machine Vision Applications (MVA). Pages 219-222. 2011.
[bibtex] [pdf]

Comparative Evaluation of Human and Active Appearance Model Based Tracking Performance of Anatomical Landmarks in Locomotion Analysis
Daniel Haase and Joachim Denzler.
Open German-Russian Workshop on Pattern Recognition and Image Understanding (OGRW). Pages 96-99. 2011.
[bibtex] [pdf]

Multi-view Active Appearance Models for the X-ray Based Analysis of Avian Bipedal Locomotion
Daniel Haase and John A. Nyakatura and Joachim Denzler.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 11-20. 2011.
[bibtex] [pdf] [abstract]

Efficient Multi-Class Incremental Learning Using Gaussian Processes
Alexander Lütz and Erik Rodner and Joachim Denzler.
Open German-Russian Workshop on Pattern Recognition and Image Understanding (OGRW). Pages 182-185. 2011.
[bibtex] [pdf] [abstract]

Spatial-Temporal Video Quality Metric Based on an Estimation of QOE
Seyed Ali Amirshahi and Mohamed-Chaker Larabi.
International Workshop on Quality of Multimedia Experience (QoMEX). Pages 84-89. 2011.
[bibtex]

Detection of Microorganisms in Complex Microscopy Images
Michael Kemmler and Björn Fröhlich and Erik Rodner and Joachim Denzler.
Open German-Russian Workshop on Pattern Recognition and Image Understanding (OGRW). Pages 115-118. 2011.
[bibtex] [pdf]

Efficient Gaussian process classification using random decision forests
Björn Fröhlich and Erik Rodner and Michael Kemmler and Joachim Denzler.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 21: pages 184-187. 2011. 10.1134/S1054661811020337
[bibtex] [pdf]

An Efficient Shortest Triangle Paths Algorithm Applied to Multi-Camera Self-Calibration
Ferid Bajramovic and Marcel Brückner and Joachim Denzler.
Journal of Mathematical Imaging and Vision (JMIV). pages 1-14. 2011.
[bibtex]

Robust Classification and Semi-Supervised Object Localization with Gaussian Processes
Alexander Lütz.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 456-461. 2011.
[bibtex] [pdf] [abstract]

Exploiting the Manhattan-world Assumption for Extrinsic Self-calibration of Multi-modal Sensor Networks
Marcel Brückner and Joachim Denzler.
International Conference on Computer Vision (ICCV). Pages 945-950. 2011.
[bibtex] [pdf]

$1/f^2$ Characteristics and Isotropy in the Fourier Power Spectra of Visual Art, Cartoons, Comics, Mangas, and Different Categories of Photographs
Michael Koch and Joachim Denzler and Christoph Redies.
PLoS ONE. 5 (8): pages e12268. 2010.
[bibtex] [abstract]

Abstract: Art images and natural scenes have in common that their radially averaged (1D) Fourier spectral power falls according to a power-law with increasing spatial frequency (1/f<sup>2</sup> characteristics), which implies that the power spectra have scale-invariant properties. In the present study, we show that other categories of man-made images, cartoons and graphic novels (comics and mangas), have similar properties. Further on, we extend our investigations to 2D power spectra. In order to determine whether the Fourier power spectra of man-made images differed from those of other categories of images (photographs of natural scenes, objects, faces and plants and scientific illustrations), we analyzed their 2D power spectra by principal component analysis. Results indicated that the first fifteen principal components allowed a partial separation of the different image categories. The differences between the image categories were studied in more detail by analyzing whether the mean power and the slope of the power gradients from low to high spatial frequencies varied across orientations in the power spectra. Mean power was generally higher in cardinal orientations both in real-world photographs and artworks, with no systematic difference between the two types of images. However, the slope of the power gradients showed a lower degree of mean variability across spectral orientations (i.e., more isotropy) in art images, cartoons and graphic novels than in photographs of comparable subject matters. Taken together, these results indicate that art images, cartoons and graphic novels possess relatively uniform 1/f<sup>2</sup> characteristics across all orientations. In conclusion, the man-made stimuli studied, which were presumably produced to evoke pleasant and/or enjoyable visual perception in human observers, form a subset of all images and share statistical properties in their Fourier power spectra. Whether these properties are necessary or sufficient to induce aesthetic perception remains to be investigated.

Online Next-Best-View Planning for Accuracy Optimization Using an Extended E-Criterion
Michael Trummer and Christoph Munkelt and Joachim Denzler.
IAPR International Conference on Pattern Recognition (ICPR). 2010.
[bibtex] [pdf]

Multi-View Planning for Simultaneous Coverage and Accuracy Optimisation
Christoph Munkelt and Andreas Breitbarth and Gunther Notni and Joachim Denzler.
British Machine Vision Conference (BMVC). Pages 118.1-118.11. 2010. doi:10.5244/C.24.118
[bibtex] [pdf]

On the Suitability of Different Features for Anomaly Detection in Wire Ropes
Esther-Sabrina Platzer and Herbert Süße and Josef Nägele and Karl-Heinz Wehking and Joachim Denzler.
Computer Vision, Imaging and Computer Graphics: Theory and Applications. Pages 296-308. 2010.
[bibtex] [pdf] [abstract]

Analysis of Structural Dependencies for the Automatic Visual Inspection of Wire Ropes
Daniel Haase and Esther-Sabrina Wacker and Ernst Günter Schukat-Talamazzini and Joachim Denzler.
International Workshop on Vision, Modelling, and Visualization (VMV). Pages 49-56. 2010.
[bibtex] [pdf] [abstract]

Semantische {S}egmentierung
Björn Fröhlich.
Informatiktage 2010: Fachwissenschaftlicher Informatik-Kongress. Pages 231-234. 2010.
[bibtex] [pdf] [abstract]

Active Self-calibration of Multi-camera Systems
Marcel Brückner and Joachim Denzler.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 31-40. 2010.
[bibtex] [pdf]

Adaptice Non-Negative Bases for Reconstruction of Spectral Data from Colorimetic Information
Seyed Hossein Amirshahi and Seyed Ali Amirshahi.
Optical Review. 17 (6): pages 562-569. 2010.
[bibtex]

Selection of Relevant Features for Raman Spectroscopy Using Supervised Classification Techniques
Michael Kemmler and Joachim Denzler.
Chemometrics in Analytical Chemistry (CAC). 2010.
[bibtex] [pdf]

An Analysis-by-Synthesis Approach to Rope Condition Monitoring
Esther-Sabrina Wacker and Joachim Denzler.
International Symposium on Visual Computing (ISVC). Pages 459-468. 2010.
[bibtex] [pdf] [abstract]

A Fast Approach for Pixelwise Labeling of Facade Images
Björn Fröhlich and Erik Rodner and Joachim Denzler.
International Conference on Pattern Recognition (ICPR). Pages 3029-3032. 2010.
[bibtex] [pdf]

One-Shot Learning of Object Categories using Dependent Gaussian Processes
Erik Rodner and Joachim Denzler.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 232-241. 2010.
[bibtex] [pdf]

Semantic Segmentation Algorithms for Aerial Image Analysis and Classification
Björn Fröhlich and Joachim Denzler.
One Day BMVA Symposium at the British Computer Society on Aerial Image Analysis and Classification. 2010.
[bibtex] [pdf]

Framework for Evaluation of Color Prints Using Image Quality Metrics
Marius Pedersen and Seyed Ali Amirshahi.
5th European Conference on Color in Graphics, Imaging and Vision, CGIV. 2010.
[bibtex]

Comparison of Various Video Quality Metrics on Different Types of Video Artifacts
Seyed Ali Amirshahi and Mohamed-Chaker Larabi.
European Workshop on Visual Information Processing, EUVIP. 2010.
[bibtex]

Multiple Kernel Gaussian Process Classification for Generic 3D Object Recognition From Time-of-Flight Images
Erik Rodner and Doaa Hegazy and Joachim Denzler.
International Conference on Image and Vision Computing. Pages 1-8. 2010.
[bibtex] [pdf] [web]

One-Class Classification with Gaussian Processes
Michael Kemmler and Erik Rodner and Joachim Denzler.
Asian Conference on Computer Vision (ACCV). Pages 489-500. 2010.
[bibtex] [pdf] [presentation]

Self-Calibration of Multi-Camera Systems
Ferid Bajramovic. 2010.
[bibtex] [abstract]

Efficient Gaussian Process Classification using Random Decision Forests
Björn Fröhlich and Erik Rodner and Michael Kemmler and Joachim Denzler.
International Conference on Pattern Recognition and Image Analysis (PRIA), St. Petersburg, Russia. Pages 93-96. 2010.
[bibtex] [pdf]

A Framework for Applying Image Quality Metrics on Printed Images
Seyed Ali Amirshahi.
Colour Research for European Advanced Technology Employment (CREATE). 2010.
[bibtex]

Classification of Microorganisms via Raman Spectroscopy Using Gaussian Processes
Michael Kemmler and Joachim Denzler and Petra Rösch and Jürgen Popp.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 81-90. 2010.
[bibtex] [pdf]

Geometric and Probabilistic Image Dissimilarity Measures for Common Field of View Detection
Marcel Brückner and Ferid Bajramovic and Joachim Denzler.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pages 2052-2057. 2009.
[bibtex] [pdf]

Guided KLT Tracking Using Camera Parameters in Consideration of Uncertainty
Michael Trummer and Joachim Denzler and Christoph Munkelt.
VISIGRAPP 2008. Pages 252-261. 2009.
[bibtex]

HMM-based Defect Localization in Wire Ropes - A new Approach to Unusual Subsequence Recognition
Esther-Sabrina Platzer and Josef Nägele and Karl-Heinz Wehking and Joachim Denzler.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 442-451. 2009.
[bibtex] [pdf] [abstract]

Combining Appearance and Range Based Information For Multi-Class Generic Object Recognition
Doaa Hegazy and Joachim Denzler.
Iberoamerican Congress on Pattern Recognition (CIARP). 2009.
[bibtex]

A Framework for Actively Selecting Viewpoints in Object Recognition
Frank Deinzer and Christian Derichs and Joachim Denzler and Heinrich Niemann.
International Journal of Pattern Recognition and Artificial Intelligence. 23 (4): pages 765-799. 2009. World Scientific Publishing
[bibtex] [pdf]

Temporal Estimation of the 3d Guide-Wire Position using 2d X-ray Images
Marcel Brückner and Frank Deinzer and Joachim Denzler.
Medical Image Computing and Computer-Assisted Intervention (MICCAI). Pages 386-393. 2009.
[bibtex] [pdf]

Learning with Few Examples by Transferring Feature Relevance
Erik Rodner and Joachim Denzler.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 252-261. 2009.
[bibtex] [pdf]

Robustness of Different Features for One-class Classification and Anomaly Detection in Wire Ropes
Esther-Sabrina Platzer and Joachim Denzler and Herbert Süße and Josef Nägele and Karl-Heinz Wehking.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 171-178. 2009.
[bibtex] [pdf]

Global Context Extraction for Object Recognition Using a Combination of Range and Visual Features
Michael Kemmler and Erik Rodner and Joachim Denzler.
Dynamic 3D Imaging Workshop. Pages 96-109. 2009.
[bibtex] [pdf]

Experimental Comparison of Wide Baseline Correspondence Algorithms for Multi Camera Calibration
Ferid Bajramovic and Michael Koch and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 458-463. 2009.
[bibtex] [pdf]

Randomized Probabilistic Latent Semantic Analysis for Scene Recognition
Erik Rodner and Joachim Denzler.
Iberoamerican Congress on Pattern Recognition (CIARP). Pages 945-953. 2009.
[bibtex] [pdf]

Principal component analysis of fourier transforms discriminates visual art from other image categories
Michael Koch and Joachim Denzler and Christoph Redies.
ECVP Abstract Supplement. Pages 49. 2009.
[bibtex] [abstract]

Generic 3D Object Recognition From Time-of-Flight Images Using Boosted Combined Shape Features
Doaa Hegazy and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). 2009.
[bibtex] [pdf]

Pedestrian Detection by Probabilistic Component Assembly
Martin Rapus and Stefan Munder and Gregory Baratoff and Joachim Denzler.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 91-100. 2009.
[bibtex] [pdf]

Extending GKLT Tracking: Feature Tracking for Controlled Environments with Integrated Uncertainty Estimation
Michael Trummer and Christoph Munkelt and Joachim Denzler.
IAPR Scandinavian Conference on Image Analysis (SCIA). Pages 460-469. 2009.
[bibtex] [pdf]

Coarse Registration of 3D Surface Triangulations Based on Moment Invariants with Applications to Object Alignment and Identification
Michael Trummer and Herbert Süße and Joachim Denzler.
IEEE International Conference on Computer Vision (ICCV). pages 1273-1279. 2009.
[bibtex] [pdf]

Using Common Field of View Detection for Multi Camera Calibration
Ferid Bajramovic and Marcel Brückner and Joachim Denzler.
International Workshop on Vision, Modelling, and Visualization (VMV). Pages 113-120. 2009.
[bibtex] [pdf]

View Planning for 3D Reconstruction Using Time-of-Flight Camera Data
Christoph Munkelt and Michael Trummer and Peter Kuehmstedt and Gunther Notni and Joachim Denzler.
Symposium of the German Association for Pattern Recognition (DAGM). 2009.
[bibtex]

Model-based Online 3D Reconstruction from Image Sequences
Olaf Kähler. 2009. ISBN: 978-3-941274-25-9
[bibtex]

Combined GKLT Feature Tracking and Reconstruction for Next Best View Planning
Michael Trummer and Christoph Munkelt and Joachim Denzler.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 161-170. 2009.
[bibtex] [pdf]

Experimentelle Auswertung von Unsicherheitsmaßen auf relativen Posen für die Multikamerakalibrierung
Ferid Bajramovic and Joachim Denzler.
Publikationen der Deutschen Gesellschaft für Photogrammetrie und Fernerkundung (DGPF), 29. Tagung, Jena 2009. Pages 119-126. 2009.
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Efficient Adaptive Combination of Histograms for Real-Time Tracking
Ferid Bajramovic and Benjamin Deutsch and Christoph Gräßl and Joachim Denzler.
EURASIP Journal on Image and Video Processing, special issue Video Tracking in Complex Scenes for Surveillance Applications. 2008: pages 1-11. 2008.
[bibtex] [pdf]

An Efficient Shortest Triangle Paths Algorithm for Uncertainty-based Multi Camera Calibration
Ferid Bajramovic and Joachim Denzler.
Workshop on Omnidirectional Vision (OMNIVIS). 2008.
[bibtex]

Difference of Boxes Filters Revisited: Shadow Suppression and Efficient Character Segmentation
Erik Rodner and Herbert Süße and Wolfgang Ortmann and Joachim Denzler.
IAPR Workshop on Document Analysis Systems. Pages 263-269. 2008.
[bibtex] [pdf] [presentation] [abstract]

New narrowband active noise control systems with significantly less computational requirements
Yegui Xiao and Maha Shadaydeh and Rabab K. Ward.
IEEE International Symposium on Circuits and Systems. Pages 41-44. 2008.
[bibtex] [web] [abstract]

Challenging Anomaly Detection in Wire Ropes Using Linear Prediction Combined with One-class Classification
Esther-Sabrina Platzer and Joachim Denzler and Herbert Süße and Josef Nägele and Karl-Heinz Wehking.
International Fall Workshop on Vision, Modelling, and Visualization (VMV). Pages 343-352. 2008.
[bibtex] [pdf] [abstract]

Reconstruction of Reflectance Spectra Using Weighted Principle Component Analysis
Farnaz Agahian and Seyed Ali Amirshahi and Seyed Hossein Amirshahi.
Color Research and Application. 33 (5): pages 360-371. 2008.
[bibtex]

IfN-Farsi: A Database of Farsi Handwritten Words
Saeed Mozaffari and Volker Märgner and Haikal El Abed and Karim Faez and Seyed Ali Amirshahi.
International Conference on Frontiers in Handwriting Recognition(ICFHR). 2008.
[bibtex]

On Fusion of Range and Intensity Information Using Graph-Cut for Planar Patch Segmentation
Olaf Kähler and Erik Rodner and Joachim Denzler.
International Journal of Intelligent Systems Technologies and Applications. 5 (3/4): pages 365-373. 2008.
[bibtex] [pdf] [abstract]

Global Uncertainty-based Selection of Relative Poses for Multi Camera Calibration
Ferid Bajramovic and Joachim Denzler.
British Machine Vision Conference (BMVC). Pages 745-754. 2008.
[bibtex] [pdf]

Learning with Few Examples using a Constrained Gaussian Prior on Randomized Trees
Erik Rodner and Joachim Denzler.
Vision, Modelling, and Visualization Workshop (VMV). Pages 159-168. 2008.
[bibtex] [pdf]

Implicit Feedback between Reconstruction and Tracking in a Combined Optimization Approach
Olaf Kähler and Joachim Denzler.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 274-283. 2008.
[bibtex] [abstract]

Experimental Evaluation of Relative Pose Estimation Algorithms
Marcel Brückner and Ferid Bajramovic and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 431-438. 2008.
[bibtex] [pdf]

Performance Comparison and Evaluation of AdaBoost and SoftBoost Algorithms on Generic Object Recognition
Doaa Hegazy and Joachim Denzler.
International Conference on Machine Learning and Pattern Recognition (MLPR). Pages 70-74. 2008.
[bibtex] [pdf]

Boosting Colored Local Features For Generic Object Recognition
Doaa Hegazy and Joachim Denzler.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 18 (2): pages 323-327. 2008.
[bibtex]

Generic Object Recognition using Boosted Combined Features
Doaa Hegazy and Joachim Denzler.
Robot Vision. 4931: pages 355-366. 2008.
[bibtex]

3D Blood Flow Reconstruction from 2D Angiograms
Esther-Sabrina Platzer and Frank Deinzer and Dietrich Paulus and Joachim Denzler.
Bildverarbeitung für die Medizin 2008 - Algorithmen, Systeme, Anwendungen. Pages 288-292. 2008.
[bibtex] [pdf] [abstract]

Extraction of fetal ECG using adaptive Volterra filters
Maha Shadaydeh and Yegui Xiao and Rabab K. Ward.
European Signal Processing Conference. Pages 1-5. 2008.
[bibtex] [pdf] [web] [abstract]

KLT Tracking Using Intrinsic and Extrinsic Camera Parameters in Consideration of Uncertainty
Michael Trummer and Joachim Denzler and Christoph Munkelt.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 346-351. 2008.
[bibtex] [pdf]

Pedestrian Recognition Using Combined Low-Resolution Depth and Intensity Images
Martin Rapus and Stefan Munder and Gregory Baratoff and Joachim Denzler.
IEEE Intelligent Vehicles Symposium. Pages 632-636. 2008.
[bibtex] [pdf] [abstract]

Robust Real-Time SFM in a Combined Formulation of Tracking and Reconstruction
Olaf Kähler and Joachim Denzler.
International Fall Workshop Vision, Modelling, and Visualization (VMV). Pages 283-292. 2008.
[bibtex] [abstract]

A New Approach for Image Quality Assessment Using SVD
Farah Torkamani-Azar and Seyed Ali Amirshahi.
9th International Symposium on Signal Processing and its Applications, ISSPA. 2007.
[bibtex]

Reading out 2D Barcode PDF417
Michael Trummer and Joachim Denzler.
Progress in Pattern Recognition, Springer, London. pages 179-185. 2007.
[bibtex] [pdf]

Self-calibration with Partially Known Rotations
Ferid Bajramovic and Joachim Denzler.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 1-10. 2007.
[bibtex] [pdf] [abstract]

Fractal-like image statistics in visual art: similarity to natural scenes
Christoph Redies and Jens Hasenstein and Joachim Denzler.
Spatial Vision. 21 (1-2): pages 97 - 117. 2007.
[bibtex] [pdf] [web]

Artists portray human faces with the Fourier statistics of complex natural scenes
Christoph Redies and Jan Hänisch and Marko Blickhan and Joachim Denzler.
Network: Computation in Neural Systems. 18 (3): pages 235-248. 2007.
[bibtex] [pdf] [web] [abstract]

Detecting Coplanar Feature Points in Handheld Image Sequences
Olaf Kähler and Joachim Denzler.
International Conference on Computer Vision Theory and Applications (VISAPP). Pages 447-452. 2007.
[bibtex] [pdf] [abstract]

Rigid Motion Constraints for Tracking Planar Objects
Olaf Kähler and Joachim Denzler.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 102-111. 2007.
[bibtex] [abstract]

Boosting Colored Local Features For Generic Object Recognition
Doaa Hegazy and Joachim Denzler.
Open German-Russian Workshop on Pattern Recognition and Image Understanding (OGRW). 2007. Extended abstract
[bibtex] [pdf]

Benchmarking 3D Reconstructions from Next Best View Planning
Christoph Munkelt and Michael Trummer and Stefan Wenhardt and Joachim Denzler.
Machine Vision Applications (MVA). Pages 552-555. 2007.
[bibtex] [pdf]

On Fusion of Range and Intensity Information Using Graph-Cut for Planar Patch Segmentation
Olaf Kähler and Erik Rodner and Joachim Denzler.
Proceedings Dynamic 3D Imaging Workshop. Pages 113-121. 2007. also appeared in International Journal of Intelligent Systems Technologies and Applications, Vol. 5, No. 3/4, pp.365-373
[bibtex] [abstract]

A Novel Approach to Affine Point Pattern Matching
Herbert Süße and Wolfgang Ortmann and Klaus Voss.
. Pages 434-444. 2006.
[bibtex] [pdf]

Detection of Planar Patches in Handheld Image Sequences
Olaf Kähler and Joachim Denzler.
Proceedings Photogrammetric Computer Vision 2006. Pages 37-42. 2006.
[bibtex] [pdf] [abstract]

A Comparison of Nearest Neighbor Search Algorithms for Generic Object Recognition
Ferid Bajramovic and Frank Mattern and Nicholas Butko and Joachim Denzler.
Advanced Concepts for Intelligent Vision Systems. Pages 1186-1197. 2006.
[bibtex] [pdf] [abstract]

An Information Theoretic Approach for Next Best View Planning in 3-D Reconstruction
Stefan Wenhardt and Benjamin Deutsch and Joachim Hornegger and Heinrich Niemann and Joachim Denzler.
International Conference on Pattern Recognition (ICPR). Pages 103-106. 2006.
[bibtex] [pdf] [abstract]

Precise 3D Measurement with Standard Means and Minimal User Interaction -- Extended Single-view Reconstruction
Michael Trummer and Joachim Denzler and Herbert Süße.
International Conference on the Application of Computer Science and Mathematics in Architecture and Civil Engineering. 2006.
[bibtex] [pdf]

Efficient Combination of Histograms for Real-Time Tracking Using Mean-Shift and Trust-Region Optimization
Ferid Bajramovic and Christoph Gräßl and Joachim Denzler.
Symposium of the German Association for Pattern Recognition (DAGM). Pages 254-261. 2005.
[bibtex] [pdf] [abstract]

Self-Organizing, Adaptive Data Fusion for 3d Object Tracking
Olaf Kähler and Joachim Denzler.
ARCS 2005 - Organic and Pervasive Computing, Workshops Proceedings. Pages 109-116. 2005.
[bibtex] [pdf]

Robust Determination of Rotation-Angles for Closed Regions Using Moments
Herbert Süße and Frank Ditrich.
. Pages 337-340. 2005.
[bibtex] [pdf]

Metrische 3-D-Vermessung einer Straßenszene mit Spezialwissen unter minimaler Interaktion -- Erweiterte monokulare Rekonstruktion
Michael Trummer and Herbert Süße and Joachim Denzler and F. Ditrich.
Publikationen der Deutschen Geselllschaft für Photogrammetrie, Fernerkundung und Geoinformation e.V.. 14: pages 39-46. 2005.
[bibtex] [pdf]