| 2025 | ECAI | LFA Applied to CNNs: Efficient Singular Value Decomposition of Convolutional Mappings by Local Fourier Analysis. | Antonia van Betteray, Matthias Rottmann, Karsten Kahl |
| 2025 | ICPRAM | Poly-MgNet: Polynomial Building Blocks in Multigrid-Inspired ResNets. | Antonia van Betteray, Matthias Rottmann, Karsten Kahl |
| 2024 | ECAI | Reducing Texture Bias of Deep Neural Networks via Edge Enhancing Diffusion. | Edgar Heinert, Matthias Rottmann, Kira Maag, Karsten Kahl |
| 2024 | WACV | Identifying Label Errors in Object Detection Datasets by Loss Inspection. | Marius Schubert, Tobias Riedlinger, Karsten Kahl, Daniel Krll, Sebastian Schoenen, Sinisa Segvic, Matthias Rottmann |
| 2024 | VISIGRAPP | Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection. | Tobias Riedlinger, Marius Schubert, Karsten Kahl, Hanno Gottschalk, Matthias Rottmann |
| 2024 | VISIGRAPP | Deep Active Learning with Noisy Oracle in Object Detection. | Marius Schubert, Tobias Riedlinger, Karsten Kahl, Matthias Rottmann |
| 2021 | IJCNN | MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection. | Marius Schubert, Karsten Kahl, Matthias Rottmann |
| 2018 | ICMLA | Deep Bayesian Active Semi-Supervised Learning. | Matthias Rottmann, Karsten Kahl, Hanno Gottschalk |