Spectral Clustering of ROIs for Object Discovery. - Paul Bodesheim (DAGM-Symposium, 2011)

Rapid Uncertainty Computation with Gaussian Processes and Histogram Intersection Kernels. - Alexander Freytag; Erik Rodner; Paul Bodesheim; Joachim Denzler (ACCV (2), 2012)

Divergence-Based One-Class Classification Using Gaussian Processes. - Paul Bodesheim; Erik Rodner; Alexander Freytag; Joachim Denzler (BMVC, 2012)

Large-Scale Gaussian Process Classification with Flexible Adaptive Histogram Kernels. - Erik Rodner; Alexander Freytag; Paul Bodesheim; Joachim Denzler (ECCV (4), 2012)

Kernel Null Space Methods for Novelty Detection. - Paul Bodesheim; Alexander Freytag; Erik Rodner; Michael Kemmler; Joachim Denzler (CVPR, 2013)

Labeling Examples That Matter: Relevance-Based Active Learning with Gaussian Processes. - Alexander Freytag; Erik Rodner; Paul Bodesheim; Joachim Denzler (GCPR, 2013)

Approximations of Gaussian Process Uncertainties for Visual Recognition Problems. - Paul Bodesheim; Alexander Freytag; Erik Rodner; Joachim Denzler (SCIA, 2013)

Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature extraction methods. - Alexander Freytag; Johannes Rühle; Paul Bodesheim; Erik Rodner; Joachim Denzler (CoRR, 2014)

Active learning and discovery of object categories in the presence of unnameable instances. - Christoph Käding; Alexander Freytag; Erik Rodner; Paul Bodesheim; Joachim Denzler (CVPR, 2015)

Ranking drivers of global carbon and energy fluxes over land. - Gustau Camps-Valls; Martin Jung 002; Kazuhito Ichii; Dario Papale; Gianluca Tramontana; Paul Bodesheim; Christopher R. Schwalm; Jakob Zscheischler; Miguel D. Mahecha; Markus Reichstein (IGARSS, 2015)

Local Novelty Detection in Multi-class Recognition Problems. - Paul Bodesheim; Alexander Freytag; Erik Rodner; Joachim Denzler (WACV, 2015)

Maximally Divergent Intervals for Anomaly Detection. - Erik Rodner; Björn Barz; Yanira Guanche; Milan Flach; Miguel D. Mahecha; Paul Bodesheim; Markus Reichstein; Joachim Denzler (CoRR, 2016)

Large-Scale Gaussian Process Inference with Generalized Histogram Intersection Kernels for Visual Recognition Tasks. - Erik Rodner; Alexander Freytag; Paul Bodesheim; Björn Fröhlich; Joachim Denzler (Int. J. Comput. Vis., 2017)

SMOS Vegetation Optical Depth and Ecosystem Functional Properties: Exploring Their Relationships in Tropical Forests. - Gaia Vaglio Laurin; Cristina Vittucci; Gianluca Tramontana; Paul Bodesheim; Paolo Ferrazzoli; Leila Guerriero; Martin Jung 002; Miguel D. Mahecha; Dario Papale (IGARSS, 2018)

Discovering unknown visual objects with novelty detection techniques. - Paul Bodesheim (Dr. Hut, 2018)

Classification-Specific Parts for Improving Fine-Grained Visual Categorization. - Dimitri Korsch; Paul Bodesheim; Joachim Denzler (GCPR, 2019)

Towards Confirmable Automated Plant Cover Determination. - Matthias Körschens; Paul Bodesheim; Christine Römermann; Solveig Franziska Bucher; Josephine Ulrich; Joachim Denzler (ECCV Workshops (6), 2020)

End-to-end Learning of a Fisher Vector Encoding for Part Features in Fine-grained Recognition. - Dimitri Korsch; Paul Bodesheim; Joachim Denzler (CoRR, 2020)

Conditional Dependence Tests Reveal the Usage of ABCD Rule Features and Bias Variables in Automatic Skin Lesion Classification. - Christian Reimers; Niklas Penzel; Paul Bodesheim; Jakob Runge; Joachim Denzler (CVPR Workshops, 2021)

End-to-End Learning of Fisher Vector Encodings for Part Features in Fine-Grained Recognition. - Dimitri Korsch; Paul Bodesheim; Joachim Denzler (GCPR, 2021)

Weakly Supervised Segmentation Pretraining for Plant Cover Prediction. - Matthias Körschens; Paul Bodesheim; Christine Römermann; Solveig Franziska Bucher; Mirco Migliavacca; Josephine Ulrich; Joachim Denzler (GCPR, 2021)

Conditional Adversarial Debiasing: Towards Learning Unbiased Classifiers from Biased Data. - Christian Reimers; Paul Bodesheim; Jakob Runge; Joachim Denzler (GCPR, 2021)

Minimizing the Annotation Effort for Detecting Wildlife in Camera Trap Images with Active Learning. - Daphne Auer; Paul Bodesheim; Christian Fiderer; Marco Heurich; Joachim Denzler (GI-Jahrestagung, 2021)

Exploiting Web Images for Moth Species Classification. - Julia Böhlke; Dimitri Korsch; Paul Bodesheim; Joachim Denzler (GI-Jahrestagung, 2021)

Deep Learning Pipeline for Automated Visual Moth Monitoring: Insect Localization and Species Classification. - Dimitri Korsch; Paul Bodesheim; Joachim Denzler (GI-Jahrestagung, 2021)

Automatic Plant Cover Estimation with Convolutional Neural Networks. - Matthias Körschens; Paul Bodesheim; Christine Römermann; Solveig Franziska Bucher; Mirco Migliavacca; Josephine Ulrich; Joachim Denzler (GI-Jahrestagung, 2021)

Lightweight Filtering of Noisy Web Data: Augmenting Fine-grained Datasets with Selected Internet Images. - Julia Böhlke; Dimitri Korsch; Paul Bodesheim; Joachim Denzler (VISIGRAPP (5: VISAPP), 2021)

Towards Learning an Unbiased Classifier from Biased Data via Conditional Adversarial Debiasing. - Christian Reimers; Paul Bodesheim; Jakob Runge; Joachim Denzler (CoRR, 2021)

Investigating Neural Network Training on a Feature Level Using Conditional Independence. - Niklas Penzel; Christian Reimers; Paul Bodesheim; Joachim Denzler (ECCV Workshops (6), 2022)

Occlusion-Robustness of Convolutional Neural Networks via Inverted Cutout. - Matthias Körschens; Paul Bodesheim; Joachim Denzler (ICPR, 2022)

Beyond Global Average Pooling: Alternative Feature Aggregations for Weakly Supervised Localization. - Matthias Körschens; Paul Bodesheim; Joachim Denzler (VISIGRAPP (4: VISAPP), 2022)

Beyond Debiasing: Actively Steering Feature Selection via Loss Regularization. - Jan Blunk; Niklas Penzel; Paul Bodesheim; Joachim Denzler (DAGM, 2023)

Automated Visual Monitoring of Nocturnal Insects with Light-based Camera Traps. - Dimitri Korsch; Paul Bodesheim; Gunnar Brehm; Joachim Denzler (CoRR, 2023)

Few-Shot Learning with Novelty Detection. - Kim Bjerge; Paul Bodesheim; Henrik Karstoft (DeLTA (1), 2024)

Determining the community composition of herbaceous species from images using convolutional neural networks. - Matthias Körschens; Solveig Franziska Bucher; Paul Bodesheim; Josephine Ulrich; Joachim Denzler; Christine Römermann (Ecol. Informatics, 2024)

Probabilistic Embeddings for Frozen Vision-Language Models: Uncertainty Quantification with Gaussian Process Latent Variable Models. - Aishwarya Venkataramanan; Paul Bodesheim; Joachim Denzler (UAI, 2025)

Deep Image Clustering with Model-Agnostic Meta-Learning. - Kim Bjerge; Paul Bodesheim; Henrik Karstoft (VISIGRAPP (2): VISAPP, 2025)