2013

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]
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]
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]
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]
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]
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]

2012

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

2011

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]
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]
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]

2010

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

2009

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]