| Entropy maximization and meta classification for out-of-distribution detection in semantic segmentation R Chan, M Rottmann, H Gottschalk Proceedings of the ieee/cvf international conference on computer vision …, 2021 | 150 | 2021 |
| Segmentmeifyoucan: A benchmark for anomaly segmentation R Chan, K Lis, S Uhlemeyer, H Blum, S Honari, R Siegwart, M Salzmann, ... Proceedings of the Neural Information Processing Systems Track on Datasets …, 2021 | 143 | 2021 |
| Prediction error meta classification in semantic segmentation: Detection via aggregated dispersion measures of softmax probabilities M Rottmann, P Colling, TP Hack, R Chan, F Hüger, P Schlicht, ... 2020 International Joint Conference on Neural Networks (IJCNN), 1-9, 2020 | 100 | 2020 |
| Application of Maximum Likelihood Decision Rules for Handling Class Imbalance in Semantic Segmentation R Chan, M Rottmann, F Hüger, P Schlicht, H Gottschalk The 30th European Safety and Reliability Conference (ESREL), 2020 | 51* | 2020 |
| Detection of false positive and false negative samples in semantic segmentation M Rottmann, K Maag, R Chan, F Hüger, P Schlicht, H Gottschalk 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2020 | 24 | 2020 |
| Controlled false negative reduction of minority classes in semantic segmentation R Chan, M Rottmann, F Hüger, P Schlicht, H Gottschalk 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 21* | 2020 |
| Two video data sets for tracking and retrieval of out of distribution objects K Maag, R Chan, S Uhlemeyer, K Kowol, H Gottschalk Proceedings of the Asian Conference on Computer Vision, 3776-3794, 2022 | 14 | 2022 |
| The ethical dilemma when (not) setting up cost-based decision rules in semantic segmentation R Chan, M Rottmann, R Dardashti, F Huger, P Schlicht, H Gottschalk Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 13 | 2019 |
| Detecting out of distribution objects in semantic segmentation of street scenes D Brüggemann, R Chan, M Rottmann, H Gottschalk, S Bracke the 30th European safety and reliability conference (ESREL) 2, 2, 2020 | 12 | 2020 |
| LU-Net: Invertible Neural Networks Based on Matrix Factorization R Chan, S Penquitt, H Gottschalk 2023 International Joint Conference on Neural Networks (IJCNN), 1-10, 2023 | 6 | 2023 |
| Detecting and learning the unknown in semantic segmentation R Chan, S Uhlemeyer, M Rottmann, H Gottschalk Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty …, 2022 | 5 | 2022 |
| What should AI see? Using the public’s opinion to determine the perception of an AI R Chan, R Dardashti, M Osinski, M Rottmann, D Brüggemann, C Rücker, ... AI and Ethics 3 (4), 1381-1405, 2023 | 4 | 2023 |
| Tryoffdiff: Virtual-try-off via high-fidelity garment reconstruction using diffusion models R Velioglu, P Bevandic, R Chan, B Hammer arXiv preprint arXiv:2411.18350, 2024 | 3 | 2024 |
| Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes Y Shoeb, R Chan, G Schwalbe, A Nowzad, F Güney, H Gottschalk Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | 3 | 2024 |
| Software architecture for human-centered reliability assessment for neural networks in autonomous driving D Brüggemann, R Chan, H Gottschalk, S Bracke 11th IMA International Conference on Modelling in Industrial Maintenance and …, 2021 | 2 | 2021 |
| FashionFail: Addressing Failure Cases in Fashion Object Detection and Segmentation R Velioglu, R Chan, B Hammer arXiv preprint arXiv:2404.08582, 2024 | 1 | 2024 |
| Detecting Anything Overlooked in Semantic Segmentation. R Chan University of Wuppertal, Germany, 2022 | 1 | 2022 |
| New advances in universal approximation with neural networks of minimal width D Rochau, H Gottschalk, R Chan arXiv preprint arXiv:2411.08735, 2024 | | 2024 |
| Uncertainty Quantification and Resource-Demanding Computer Vision Applications of Deep Learning J Burghoff, R Chan, H Gottschalk, A Muetze, T Riedlinger, M Rottmann, ... arXiv preprint arXiv:2205.14917, 2022 | | 2022 |
| Ansätze zur Verbesserung KI-basierter Systeme für das autonome Fahren D Brüggemann, S Bracke, H Gottschalk, M Rottmann, K Maag, R Chan, ... Qualitätsmanagement in den 20er Jahren-Trends und Perspektiven: Bericht zur …, 2021 | | 2021 |
Hanno GottschalkProfessor for Mathematical Modeling of Industrial Life Cycles, TU BerlinBestätigte E-Mail-Adresse bei math.tu-berlin.de