Paul Bodesheim

45 papers A* 2A 3B 1C 2Journal 14Unranked 22

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	LEPY: A Python pipeline for automated trait extraction from standardised Lepidoptera images. Ecol. Informatics Yenny Correa-Carmona, Dennis Böttger, Dimitri Korsch, Kim L. Holzmann, Pedro Alonso-Alonso, Andrea Pinos, Felipe Yon, Alexander Keller, Ingolf Steffan-Dewenter, Paul Bodesheim, Marcell K. Peters, Gunnar Brehm
2025	—	`conf`	Adaptive Model Selection for Expanded Post Hoc Debiasing and Mitigating Varying Degrees of Spurious Correlations. CAIP (2) Jan Blunk, Paul Bodesheim, Joachim Denzler
2025	—	`conf`	Deep Image Clustering with Model-Agnostic Meta-Learning. VISIGRAPP (2): VISAPP Kim Bjerge, Paul Bodesheim, Henrik Karstoft
2025	J	`jnl`	PlantCAPNet: A deep learning system for image-based plant cover and phenology analysis. Ecol. Informatics Matthias Körschens, Solveig Franziska Bucher, Paul Bodesheim, Joachim Denzler, Christine Römermann
2025	A	`conf`	Probabilistic Embeddings for Frozen Vision-Language Models: Uncertainty Quantification with Gaussian Process Latent Variable Models. UAI Aishwarya Venkataramanan, Paul Bodesheim, Joachim Denzler
2025	J	`jnl`	Probabilistic Embeddings for Frozen Vision-Language Models: Uncertainty Quantification with Gaussian Process Latent Variable Models. CoRR Aishwarya Venkataramanan, Paul Bodesheim, Joachim Denzler
2025	J	`jnl`	Saccadic Vision for Fine-Grained Visual Classification. CoRR Johann Schmidt, Sebastian Stober, Joachim Denzler, Paul Bodesheim
2024	J	`jnl`	Determining the community composition of herbaceous species from images using convolutional neural networks. Ecol. Informatics Matthias Körschens, Solveig Franziska Bucher, Paul Bodesheim, Josephine Ulrich, Joachim Denzler, Christine Römermann
2024	—	`conf`	Few-Shot Learning with Novelty Detection. DeLTA (1) Kim Bjerge, Paul Bodesheim, Henrik Karstoft
2023	J	`jnl`	Automated Visual Monitoring of Nocturnal Insects with Light-based Camera Traps. CoRR Dimitri Korsch, Paul Bodesheim, Gunnar Brehm, Joachim Denzler
2023	—	`conf`	Beyond Debiasing: Actively Steering Feature Selection via Loss Regularization. DAGM Jan Blunk, Niklas Penzel, Paul Bodesheim, Joachim Denzler
2023	J	`jnl`	Deep Learning Pipeline for Automated Visual Moth Monitoring: Insect Localization and Species Classification. CoRR Dimitri Korsch, Paul Bodesheim, Joachim Denzler
2022	—	`conf`	Beyond Global Average Pooling: Alternative Feature Aggregations for Weakly Supervised Localization. VISIGRAPP (4: VISAPP) Matthias Körschens, Paul Bodesheim, Joachim Denzler
2022	—	`conf`	Investigating Neural Network Training on a Feature Level Using Conditional Independence. ECCV Workshops (6) Niklas Penzel, Christian Reimers, Paul Bodesheim, Joachim Denzler
2022	B	`conf`	Occlusion-Robustness of Convolutional Neural Networks via Inverted Cutout. ICPR Matthias Körschens, Paul Bodesheim, Joachim Denzler
2021	—	`conf`	Automatic Plant Cover Estimation with Convolutional Neural Networks. GI-Jahrestagung Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Mirco Migliavacca, Josephine Ulrich, Joachim Denzler
2021	J	`jnl`	Automatic Plant Cover Estimation with Convolutional Neural Networks. CoRR Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Mirco Migliavacca, Josephine Ulrich, Joachim Denzler
2021	—	`conf`	Conditional Adversarial Debiasing: Towards Learning Unbiased Classifiers from Biased Data. GCPR Christian Reimers, Paul Bodesheim, Jakob Runge, Joachim Denzler
2021	—	`conf`	Conditional Dependence Tests Reveal the Usage of ABCD Rule Features and Bias Variables in Automatic Skin Lesion Classification. CVPR Workshops Christian Reimers, Niklas Penzel, Paul Bodesheim, Jakob Runge, Joachim Denzler
2021	—	`conf`	Deep Learning Pipeline for Automated Visual Moth Monitoring: Insect Localization and Species Classification. GI-Jahrestagung Dimitri Korsch, Paul Bodesheim, Joachim Denzler
2021	—	`conf`	End-to-End Learning of Fisher Vector Encodings for Part Features in Fine-Grained Recognition. GCPR Dimitri Korsch, Paul Bodesheim, Joachim Denzler
2021	—	`conf`	Exploiting Web Images for Moth Species Classification. GI-Jahrestagung Julia Böhlke, Dimitri Korsch, Paul Bodesheim, Joachim Denzler
2021	—	`conf`	Lightweight Filtering of Noisy Web Data: Augmenting Fine-grained Datasets with Selected Internet Images. VISIGRAPP (5: VISAPP) Julia Böhlke, Dimitri Korsch, Paul Bodesheim, Joachim Denzler
2021	—	`conf`	Minimizing the Annotation Effort for Detecting Wildlife in Camera Trap Images with Active Learning. GI-Jahrestagung Daphne Auer, Paul Bodesheim, Christian Fiderer, Marco Heurich, Joachim Denzler
2021	J	`jnl`	Towards Learning an Unbiased Classifier from Biased Data via Conditional Adversarial Debiasing. CoRR Christian Reimers, Paul Bodesheim, Jakob Runge, Joachim Denzler
2021	—	`conf`	Weakly Supervised Segmentation Pretraining for Plant Cover Prediction. GCPR Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Mirco Migliavacca, Josephine Ulrich, Joachim Denzler
2020	J	`jnl`	End-to-end Learning of a Fisher Vector Encoding for Part Features in Fine-grained Recognition. CoRR Dimitri Korsch, Paul Bodesheim, Joachim Denzler
2020	—	`conf`	Towards Confirmable Automated Plant Cover Determination. ECCV Workshops (6) Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Josephine Ulrich, Joachim Denzler
2019	—	`conf`	Classification-Specific Parts for Improving Fine-Grained Visual Categorization. GCPR Dimitri Korsch, Paul Bodesheim, Joachim Denzler
2019	J	`jnl`	Classification-Specific Parts for Improving Fine-Grained Visual Categorization. CoRR Dimitri Korsch, Paul Bodesheim, Joachim Denzler
2018	—	`—`	Discovering unknown visual objects with novelty detection techniques. Paul Bodesheim
2018	C	`conf`	SMOS Vegetation Optical Depth and Ecosystem Functional Properties: Exploring Their Relationships in Tropical Forests. IGARSS Gaia Vaglio Laurin, Cristina Vittucci, Gianluca Tramontana, Paul Bodesheim, Paolo Ferrazzoli, Leila Guerriero, Martin Jung, Miguel D. Mahecha, Dario Papale
2017	J	`jnl`	Large-Scale Gaussian Process Inference with Generalized Histogram Intersection Kernels for Visual Recognition Tasks. Int. J. Comput. Vis. Erik Rodner, Alexander Freytag, Paul Bodesheim, Björn Fröhlich, Joachim Denzler
2016	J	`jnl`	Maximally Divergent Intervals for Anomaly Detection. CoRR Erik Rodner, Björn Barz, Yanira Guanche, Milan Flach, Miguel D. Mahecha, Paul Bodesheim, Markus Reichstein, Joachim Denzler
2015	A*	`conf`	Active learning and discovery of object categories in the presence of unnameable instances. CVPR Christoph Käding, Alexander Freytag, Erik Rodner, Paul Bodesheim, Joachim Denzler
2015	A	`conf`	Local Novelty Detection in Multi-class Recognition Problems. WACV Paul Bodesheim, Alexander Freytag, Erik Rodner, Joachim Denzler
2015	C	`conf`	Ranking drivers of global carbon and energy fluxes over land. IGARSS Gustau Camps-Valls, Martin Jung, Kazuhito Ichii, Dario Papale, Gianluca Tramontana, Paul Bodesheim, Christopher R. Schwalm, Jakob Zscheischler, Miguel D. Mahecha, Markus Reichstein
2014	J	`jnl`	Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature extraction methods. CoRR Alexander Freytag, Johannes Rühle, Paul Bodesheim, Erik Rodner, Joachim Denzler
2013	—	`conf`	Approximations of Gaussian Process Uncertainties for Visual Recognition Problems. SCIA Paul Bodesheim, Alexander Freytag, Erik Rodner, Joachim Denzler
2013	A*	`conf`	Kernel Null Space Methods for Novelty Detection. CVPR Paul Bodesheim, Alexander Freytag, Erik Rodner, Michael Kemmler, Joachim Denzler
2013	—	`conf`	Labeling Examples That Matter: Relevance-Based Active Learning with Gaussian Processes. GCPR Alexander Freytag, Erik Rodner, Paul Bodesheim, Joachim Denzler
2012	A	`conf`	Divergence-Based One-Class Classification Using Gaussian Processes. BMVC Paul Bodesheim, Erik Rodner, Alexander Freytag, Joachim Denzler
2012	—	`conf`	Large-Scale Gaussian Process Classification with Flexible Adaptive Histogram Kernels. ECCV (4) Erik Rodner, Alexander Freytag, Paul Bodesheim, Joachim Denzler
2012	—	`conf`	Rapid Uncertainty Computation with Gaussian Processes and Histogram Intersection Kernels. ACCV (2) Alexander Freytag, Erik Rodner, Paul Bodesheim, Joachim Denzler
2011	—	`conf`	Spectral Clustering of ROIs for Object Discovery. DAGM-Symposium Paul Bodesheim

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.