| Time-dynamic estimates of the reliability of deep semantic segmentation networks K Maag, M Rottmann, H Gottschalk 2020 IEEE 32nd International Conference on Tools with Artificial …, 2020 | 40 | 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 |
| An unsupervised temporal consistency (TC) loss to improve the performance of semantic segmentation networks S Varghese, S Gujamagadi, M Klingner, N Kapoor, A Bar, JD Schneider, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 21 | 2021 |
| 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 |
| Improving video instance segmentation by light-weight temporal uncertainty estimates K Maag, M Rottmann, S Varghese, F Hüger, P Schlicht, H Gottschalk 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 12 | 2021 |
| Pixel-wise Gradient Uncertainty for Convolutional Neural Networks applied to Out-of-Distribution Segmentation K Maag, T Riedlinger Proceedings of the 19th International Joint Conference on Computer Vision …, 2024 | 6 | 2024 |
| Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation K Maag, A Fischer Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | 5 | 2024 |
| Uncertainty-based Detection of Adversarial Attacks in Semantic Segmentation K Maag, A Fischer Proceedings of the 19th International Joint Conference on Computer Vision …, 2024 | 5 | 2024 |
| False negative reduction in video instance segmentation using uncertainty estimates K Maag 2021 IEEE 33rd International Conference on Tools with Artificial …, 2021 | 5 | 2021 |
| Reducing Texture Bias of Deep Neural Networks via Edge Enhancing Diffusion E Heinert, M Rottmann, K Maag, K Kahl arXiv preprint arXiv:2402.09530, 2024 | 3 | 2024 |
| False Negative Reduction in Semantic Segmentation under Domain Shift using Depth Estimation K Maag, M Rottmann Proceedings of the 18th International Joint Conference on Computer Vision …, 2023 | 3 | 2023 |
| Detection of iterative adversarial attacks via counter attack M Rottmann, K Maag, M Peyron, H Gottschalk, N Krejić Journal of Optimization Theory and Applications, 1-38, 2023 | 2 | 2023 |
| Prediction Rating and Performance Improvement for Segmentation Networks by Time-Dynamic Uncertainty Estimates. K Maag University of Wuppertal, Germany, 2021 | 1 | 2021 |
| Multi-Scale Foreground-Background Confidence for Out-of-Distribution Segmentation S Marschall, K Maag arXiv preprint arXiv:2412.16990, 2024 | | 2024 |
| Integrating uncertainty quantification into randomized smoothing based robustness guarantees S Däubener, K Maag, D Krueger, A Fischer arXiv preprint arXiv:2410.20432, 2024 | | 2024 |
| Detecting Adversarial Attacks in Semantic Segmentation via Uncertainty Estimation: A Deep Analysis K Maag, R Resner, A Fischer arXiv preprint arXiv:2408.10021, 2024 | | 2024 |
| 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 BerlinEmail verificata su math.tu-berlin.de