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Active Learning for Regression Tasks with Expected Model Output Changes.
British Machine Vision Conference (BMVC). 2018. [bibtex] [pdf] [code] [supplementary] [abstract] |
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Finding the Unknown: Novelty Detection with Extreme Value Signatures of Deep Neural Activations.
German Conference on Pattern Recognition (GCPR). Pages 226-238. 2017. [bibtex] [pdf] [supplementary] [abstract] |
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Large-Scale Gaussian Process Inference with Generalized Histogram Intersection Kernels for Visual Recognition Tasks.
International Journal of Computer Vision (IJCV). 121 (2): pages 253-280. 2017. [bibtex] [pdf] [web] |
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Lifelong Learning for Visual Recognition Systems.
(2016) ISBN 9783843929950 [bibtex] [pdf] [web] |
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Fine-tuning Deep Neural Networks in Continuous Learning Scenarios.
ACCV Workshop on Interpretation and Visualization of Deep Neural Nets (ACCV-WS). 2016. [bibtex] [pdf] [web] [supplementary] [abstract] |
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Large-scale Active Learning with Approximated Expected Model Output Changes.
German Conference on Pattern Recognition (GCPR). Pages 179-191. 2016. [bibtex] [pdf] [web] [code] [supplementary] [abstract] |
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Active and Continuous Exploration with Deep Neural Networks and Expected Model Output Changes.
NIPS Workshop on Continual Learning and Deep Networks (NIPS-WS). 2016. [bibtex] [pdf] [web] [abstract] |
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Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates.
German Conference on Pattern Recognition (GCPR). Pages 51-63. 2016. [bibtex] [pdf] [web] [supplementary] [abstract] |
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Watch, Ask, Learn, and Improve: A Lifelong Learning Cycle for Visual Recognition.
European Symposium on Artificial Neural Networks (ESANN). Pages 381-386. 2016. [bibtex] [pdf] [code] [presentation] [abstract] |
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Active Learning and Discovery of Object Categories in the Presence of Unnameable Instances.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pages 4343-4352. 2015. [bibtex] [pdf] [web] [code] [presentation] [supplementary] [abstract] |
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Local Novelty Detection in Multi-class Recognition Problems.
IEEE Winter Conference on Applications of Computer Vision (WACV). Pages 813-820. 2015. [bibtex] [pdf] [supplementary] |
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Interactive Image Retrieval for Biodiversity Research.
German Conference on Pattern Recognition (GCPR). Pages 129-141. 2015. [bibtex] [pdf] [abstract] |
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Birds of a Feather Flock Together - Local Learning of Mid-level Representations for Fine-grained Recognition.
ECCV Workshop on Parts and Attributes (ECCV-WS). 2014. [bibtex] [pdf] [web] [code] [presentation] |
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Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature extraction methods.
International Conference on Pattern Recognition (ICPR) - FEAST workshop. 2014. Best Poster Award [bibtex] [pdf] [code] [presentation] [abstract] |
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Selecting Influential Examples: Active Learning with Expected Model Output Changes.
European Conference on Computer Vision (ECCV). Pages 562-577. 2014. [bibtex] [pdf] [presentation] [supplementary] [abstract] |
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Exemplar-specific Patch Features for Fine-grained Recognition.
German Conference on Pattern Recognition (GCPR). Pages 144-156. 2014. [bibtex] [pdf] [code] [supplementary] [abstract] |
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Nonparametric Part Transfer for Fine-grained Recognition.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pages 2489-2496. 2014. [bibtex] [pdf] [web] [code] [presentation] [abstract] |
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Approximations of Gaussian Process Uncertainties for Visual Recognition Problems.
Scandinavian Conference on Image Analysis (SCIA). Pages 182-194. 2013. [bibtex] [pdf] |
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An Efficient Approximation for Gaussian Process Regression.
(2013) Technical Report TR-FSU-INF-CV-2013-01 [bibtex] [pdf] |
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Kernel Null Space Methods for Novelty Detection.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pages 3374-3381. 2013. [bibtex] [pdf] [web] [code] [presentation] |
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Fine-grained Categorization - Short Summary of our Entry for the ImageNet Challenge 2012.
arXiv preprint arXiv:1310.4759. 2013. [bibtex] [pdf] [web] |
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Beyond the closed-world assumption: The importance of novelty detection and open set recognition.
GCPR Workshop on Unsolved Problems in Pattern Recognition (GCPR-WS). 2013. [bibtex] [pdf] |
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Labeling examples that matter: Relevance-Based Active Learning with Gaussian Processes.
German Conference on Pattern Recognition (GCPR). Pages 282-291. 2013. [bibtex] [pdf] [code] [supplementary] [abstract] |
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Efficient Semantic Segmentation with Gaussian Processes and Histogram Intersection Kernels.
International Conference on Pattern Recognition (ICPR). Pages 3313-3316. 2012. [bibtex] [pdf] |
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Large-Scale Gaussian Process Classification with Flexible Adaptive Histogram Kernels.
European Conference on Computer Vision (ECCV). Pages 85-98. 2012. [bibtex] [pdf] [supplementary] |
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Beyond Classification - Large-scale Gaussian Process Inference and Uncertainty Prediction.
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 abstract of our ACCV'12 paper. [bibtex] [pdf] |
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Rapid Uncertainty Computation with Gaussian Processes and Histogram Intersection Kernels.
Asian Conference on Computer Vision (ACCV). Pages 511-524. 2012. Best Paper Honorable Mention Award [bibtex] [pdf] [presentation] |
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Divergence-Based One-Class Classification Using Gaussian Processes.
British Machine Vision Conference (BMVC). Pages 50.1-50.11. 2012. http://dx.doi.org/10.5244/C.26.50 [bibtex] [pdf] [presentation] |