| Superpixels: An evaluation of the state-of-the-art D Stutz, A Hermans, B Leibe Computer Vision and Image Understanding 166, 1-27, 2018 | 663 | 2018 |
| Capabilities of gemini models in medicine K Saab, T Tu, WH Weng, R Tanno, D Stutz, E Wulczyn, F Zhang, ... arXiv preprint arXiv:2404.18416, 2024 | 393 | 2024 |
| Disentangling adversarial robustness and generalization D Stutz, M Hein, B Schiele Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 388 | 2019 |
| Understanding convolutional neural networks D Stutz Seminar Report, Visual Computing Institute, RWTH Aachen University, 2014 | 313* | 2014 |
| Learning 3d shape completion from laser scan data with weak supervision D Stutz, A Geiger Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 299 | 2018 |
| Confidence-calibrated adversarial training: Generalizing to unseen attacks D Stutz, M Hein, B Schiele International conference on machine learning, 9155-9166, 2020 | 188 | 2020 |
| Learning optimal conformal classifiers D Stutz, AT Cemgil, A Doucet arXiv preprint arXiv:2110.09192, 2021 | 145 | 2021 |
| Adversarial training against location-optimized adversarial patches S Rao, D Stutz, B Schiele European conference on computer vision, 429-448, 2020 | 122 | 2020 |
| Learning 3D Shape Completion Under Weak Supervision D Stutz, A Geiger International Journal of Computer Vision, 2018 | 118 | 2018 |
| Imagen 3 J Baldridge, J Bauer, M Bhutani, N Brichtova, A Bunner, L Castrejon, ... arXiv preprint arXiv:2408.07009, 2024 | 90 | 2024 |
| Relating adversarially robust generalization to flat minima D Stutz, M Hein, B Schiele Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 86 | 2021 |
| Superpixel segmentation: An evaluation D Stutz German conference on pattern recognition, 555-562, 2015 | 47 | 2015 |
| Mitigating llm hallucinations via conformal abstention YA Yadkori, I Kuzborskij, D Stutz, A György, A Fisch, A Doucet, ... arXiv preprint arXiv:2405.01563, 2024 | 45 | 2024 |
| Bit error robustness for energy-efficient dnn accelerators D Stutz, N Chandramoorthy, M Hein, B Schiele Proceedings of Machine Learning and Systems 3, 569-598, 2021 | 45 | 2021 |
| Robustifying token attention for vision transformers Y Guo, D Stutz, B Schiele Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 44 | 2023 |
| Capabilities of Gemini models in medicine (2024) K Saab, T Tu, WH Weng, R Tanno, D Stutz, E Wulczyn, F Zhang, ... arXiv preprint arXiv:2404.18416, 2024 | 42 | 2024 |
| Improving robustness of vision transformers by reducing sensitivity to patch corruptions Y Guo, D Stutz, B Schiele Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 39 | 2023 |
| Conformal prediction under ambiguous ground truth D Stutz, AG Roy, T Matejovicova, P Strachan, AT Cemgil, A Doucet arXiv preprint arXiv:2307.09302, 2023 | 29 | 2023 |
| Superpixel segmentation using depth information D Stutz RWTH Aachen University, Aachen, Germany, 2014 | 28 | 2014 |
| Random and adversarial bit error robustness: Energy-efficient and secure DNN accelerators D Stutz, N Chandramoorthy, M Hein, B Schiele IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (3), 3632-3647, 2022 | 27 | 2022 |
Bernt SchieleProfessor, Max Planck Institute for Informatics, Saarland University, Saarland Informatics CampusVerified email at mpi-inf.mpg.de
