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2020 – today
- 2024
[j2]Matthias Körschens, Solveig Franziska Bucher, Paul Bodesheim, Josephine Ulrich, Joachim Denzler, Christine Römermann:
Determining the community composition of herbaceous species from images using convolutional neural networks. Ecol. Informatics 80: 102516 (2024)- [c27]Kim Bjerge, Paul Bodesheim, Henrik Karstoft:
Few-Shot Learning with Novelty Detection. DeLTA (1) 2024: 340-363 - 2023
- [c26]Jan Blunk
, Niklas Penzel, Paul Bodesheim, Joachim Denzler:
Beyond Debiasing: Actively Steering Feature Selection via Loss Regularization. DAGM 2023: 394-408 - [i8]Dimitri Korsch, Paul Bodesheim, Joachim Denzler:
Deep Learning Pipeline for Automated Visual Moth Monitoring: Insect Localization and Species Classification. CoRR abs/2307.15427 (2023) - [i7]Dimitri Korsch, Paul Bodesheim, Gunnar Brehm, Joachim Denzler:
Automated Visual Monitoring of Nocturnal Insects with Light-based Camera Traps. CoRR abs/2307.15433 (2023) - 2022
- [c25]Niklas Penzel, Christian Reimers, Paul Bodesheim, Joachim Denzler:
Investigating Neural Network Training on a Feature Level Using Conditional Independence. ECCV Workshops (6) 2022: 383-399 - [c24]Matthias Körschens, Paul Bodesheim, Joachim Denzler:
Occlusion-Robustness of Convolutional Neural Networks via Inverted Cutout. ICPR 2022: 2829-2835 - [c23]Matthias Körschens, Paul Bodesheim, Joachim Denzler:
Beyond Global Average Pooling: Alternative Feature Aggregations for Weakly Supervised Localization. VISIGRAPP (4: VISAPP) 2022: 180-191 - 2021
- [c22]Christian Reimers, Niklas Penzel, Paul Bodesheim, Jakob Runge, Joachim Denzler:
Conditional Dependence Tests Reveal the Usage of ABCD Rule Features and Bias Variables in Automatic Skin Lesion Classification. CVPR Workshops 2021: 1810-1819 - [c21]Christian Reimers, Paul Bodesheim, Jakob Runge, Joachim Denzler:
Conditional Adversarial Debiasing: Towards Learning Unbiased Classifiers from Biased Data. GCPR 2021: 48-62 - [c20]Dimitri Korsch, Paul Bodesheim, Joachim Denzler:
End-to-End Learning of Fisher Vector Encodings for Part Features in Fine-Grained Recognition. GCPR 2021: 142-158 - [c19]Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Mirco Migliavacca, Josephine Ulrich, Joachim Denzler:
Weakly Supervised Segmentation Pretraining for Plant Cover Prediction. GCPR 2021: 589-603 - [c18]Dimitri Korsch, Paul Bodesheim, Joachim Denzler:
Deep Learning Pipeline for Automated Visual Moth Monitoring: Insect Localization and Species Classification. GI-Jahrestagung 2021: 443-460 - [c17]Julia Böhlke, Dimitri Korsch, Paul Bodesheim, Joachim Denzler:
Exploiting Web Images for Moth Species Classification. GI-Jahrestagung 2021: 481-498 - [c16]Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Mirco Migliavacca, Josephine Ulrich, Joachim Denzler:
Automatic Plant Cover Estimation with Convolutional Neural Networks. GI-Jahrestagung 2021: 499-516 - [c15]Daphne Auer, Paul Bodesheim, Christian Fiderer, Marco Heurich, Joachim Denzler:
Minimizing the Annotation Effort for Detecting Wildlife in Camera Trap Images with Active Learning. GI-Jahrestagung 2021: 547-564 - [c14]Julia Böhlke, Dimitri Korsch, Paul Bodesheim, Joachim Denzler:
Lightweight Filtering of Noisy Web Data: Augmenting Fine-grained Datasets with Selected Internet Images. VISIGRAPP (5: VISAPP) 2021: 466-477 - [i6]Christian Reimers, Paul Bodesheim, Jakob Runge, Joachim Denzler:
Towards Learning an Unbiased Classifier from Biased Data via Conditional Adversarial Debiasing. CoRR abs/2103.06179 (2021) - [i5]Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Mirco Migliavacca, Josephine Ulrich, Joachim Denzler:
Automatic Plant Cover Estimation with Convolutional Neural Networks. CoRR abs/2106.11154 (2021) - 2020
- [c13]Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Josephine Ulrich, Joachim Denzler:
Towards Confirmable Automated Plant Cover Determination. ECCV Workshops (6) 2020: 312-329 - [i4]Dimitri Korsch, Paul Bodesheim, Joachim Denzler:
End-to-end Learning of a Fisher Vector Encoding for Part Features in Fine-grained Recognition. CoRR abs/2007.02080 (2020)
2010 – 2019
- 2019
- [c12]Dimitri Korsch, Paul Bodesheim, Joachim Denzler:
Classification-Specific Parts for Improving Fine-Grained Visual Categorization. GCPR 2019: 62-75 - [i3]Dimitri Korsch, Paul Bodesheim, Joachim Denzler:
Classification-Specific Parts for Improving Fine-Grained Visual Categorization. CoRR abs/1909.07075 (2019) - 2018
- [b1]Paul Bodesheim:
Discovering unknown visual objects with novelty detection techniques. University of Jena, Germany, Dr. Hut 2018, ISBN 978-3-8439-3546-3, pp. 1-487 - [c11]Gaia Vaglio Laurin, Cristina Vittucci, Gianluca Tramontana, Paul Bodesheim, Paolo Ferrazzoli, Leila Guerriero, Martin Jung, Miguel D. Mahecha, Dario Papale:
SMOS Vegetation Optical Depth and Ecosystem Functional Properties: Exploring Their Relationships in Tropical Forests. IGARSS 2018: 5891-5894 - 2017
- [j1]Erik Rodner, Alexander Freytag, Paul Bodesheim, Björn Fröhlich, Joachim Denzler:
Large-Scale Gaussian Process Inference with Generalized Histogram Intersection Kernels for Visual Recognition Tasks. Int. J. Comput. Vis. 121(2): 253-280 (2017) - 2016
- [i2]Erik Rodner, Björn Barz, Yanira Guanche, Milan Flach, Miguel D. Mahecha, Paul Bodesheim, Markus Reichstein, Joachim Denzler:
Maximally Divergent Intervals for Anomaly Detection. CoRR abs/1610.06761 (2016) - 2015
- [c10]Christoph Käding, Alexander Freytag, Erik Rodner, Paul Bodesheim, Joachim Denzler:
Active learning and discovery of object categories in the presence of unnameable instances. CVPR 2015: 4343-4352 - [c9]Gustau Camps-Valls, Martin Jung, Kazuhito Ichii, Dario Papale, Gianluca Tramontana, Paul Bodesheim, Christopher R. Schwalm, Jakob Zscheischler, Miguel D. Mahecha, Markus Reichstein:
Ranking drivers of global carbon and energy fluxes over land. IGARSS 2015: 4416-4419 - [c8]Paul Bodesheim, Alexander Freytag, Erik Rodner, Joachim Denzler:
Local Novelty Detection in Multi-class Recognition Problems. WACV 2015: 813-820 - 2014
- [i1]Alexander Freytag, Johannes Rühle, Paul Bodesheim, Erik Rodner, Joachim Denzler:
Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature extraction methods. CoRR abs/1408.4692 (2014) - 2013
- [c7]Paul Bodesheim, Alexander Freytag, Erik Rodner, Michael Kemmler, Joachim Denzler:
Kernel Null Space Methods for Novelty Detection. CVPR 2013: 3374-3381 - [c6]Alexander Freytag, Erik Rodner, Paul Bodesheim, Joachim Denzler:
Labeling Examples That Matter: Relevance-Based Active Learning with Gaussian Processes. GCPR 2013: 282-291 - [c5]Paul Bodesheim, Alexander Freytag, Erik Rodner, Joachim Denzler:
Approximations of Gaussian Process Uncertainties for Visual Recognition Problems. SCIA 2013: 182-194 - 2012
- [c4]Alexander Freytag, Erik Rodner, Paul Bodesheim, Joachim Denzler:
Rapid Uncertainty Computation with Gaussian Processes and Histogram Intersection Kernels. ACCV (2) 2012: 511-524 - [c3]Paul Bodesheim, Erik Rodner, Alexander Freytag, Joachim Denzler:
Divergence-Based One-Class Classification Using Gaussian Processes. BMVC 2012: 1-11 - [c2]Erik Rodner, Alexander Freytag, Paul Bodesheim, Joachim Denzler:
Large-Scale Gaussian Process Classification with Flexible Adaptive Histogram Kernels. ECCV (4) 2012: 85-98 - 2011
- [c1]Paul Bodesheim:
Spectral Clustering of ROIs for Object Discovery. DAGM-Symposium 2011: 450-455
Coauthor Index
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