| On the p-Laplacian and ∞-Laplacian on Graphs with Applications in Image and Data Processing A Elmoataz, M Toutain, D Tenbrinck SIAM Journal on Imaging Sciences 8 (4), 2412-2451, 2015 | 149 | 2015 |
| On the p-Laplacian and ∞-Laplacian on Graphs with Applications in Image and Data Processing A Elmoataz, M Toutain, D Tenbrinck SIAM Journal on Imaging Sciences 8 (4), 2412-2451, 2015 | 149 | 2015 |
| A variational framework for region-based segmentation incorporating physical noise models A Sawatzky, D Tenbrinck, X Jiang, M Burger Journal of Mathematical Imaging and Vision 47 (3), 179-209, 2013 | 53 | 2013 |
| CLIP: Cheap Lipschitz Training of Neural Networks L Bungert, R Raab, T Roith, L Schwinn, D Tenbrinck International Conference on Scale Space and Variational Methods in Computer …, 2021 | 40 | 2021 |
| CLIP: Cheap Lipschitz training of neural networks L Bungert, R Raab, T Roith, L Schwinn, D Tenbrinck International Conference on Scale Space and Variational Methods in Computer …, 2021 | 40 | 2021 |
| Fenchel duality theory and a primal-dual algorithm on Riemannian manifolds R Bergmann, R Herzog, MS Louzeiro, D Tenbrinck, J Vidal-Núñez Foundations of Computational Mathematics, 1-40, 2021 | 29* | 2021 |
| A Bregman learning framework for sparse neural networks L Bungert, T Roith, D Tenbrinck, M Burger Journal of Machine Learning Research 23 (192), 1-43, 2022 | 27 | 2022 |
| Histogram-based optical flow for motion estimation in ultrasound imaging D Tenbrinck, S Schmid, X Jiang, K Schäfers, J Stypmann Journal of mathematical imaging and vision 47 (1), 138-150, 2013 | 27 | 2013 |
| A Graph Framework for Manifold-valued Data R Bergmann, D Tenbrinck SIAM Journal on Imaging Sciences 11 (1), 325-360, 2018 | 26 | 2018 |
| Image segmentation with arbitrary noise models by solving minimal surface problems D Tenbrinck, X Jiang Pattern Recognition 48 (11), 3293-3309, 2015 | 21 | 2015 |
| Computing nonlinear eigenfunctions via gradient flow extinction L Bungert, M Burger, D Tenbrinck Scale Space and Variational Methods in Computer Vision: 7th International …, 2019 | 16 | 2019 |
| Identifying untrustworthy predictions in neural networks by geometric gradient analysis L Schwinn, A Nguyen, R Raab, L Bungert, D Tenbrinck, D Zanca, ... Uncertainty in Artificial Intelligence, 854-864, 2021 | 15 | 2021 |
| Impact of Physical Noise Modeling on Image Segmentation in Echocardiography. D Tenbrinck, A Sawatzky, X Jiang, M Burger, W Haffner, P Willems, ... VCBM, 33-40, 2012 | 15 | 2012 |
| Resolution-Invariant Image Classification based on Fourier Neural Operators S Kabri, T Roith, D Tenbrinck, M Burger Scale Space and Variational Methods in Computer Vision: 9th International …, 2023 | 11 | 2023 |
| Dynamically sampled nonlocal gradients for stronger adversarial attacks L Schwinn, A Nguyen, R Raab, D Zanca, BM Eskofier, D Tenbrinck, ... 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 11 | 2021 |
| Using migrating cells as probes to illuminate features in live embryonic tissues S Gross-Thebing, L Truszkowski, D Tenbrinck, H Sánchez-Iranzo, ... Science Advances 6 (49), eabc5546, 2020 | 10 | 2020 |
| Biomedical imaging: a computer vision perspective X Jiang, M Dawood, F Gigengack, B Risse, S Schmid, D Tenbrinck, ... Computer Analysis of Images and Patterns: 15th International Conference …, 2013 | 9 | 2013 |
| The Infinity Laplacian Eigenvalue Problem: Reformulation and a Numerical Scheme F Bozorgnia, L Bungert, D Tenbrinck Journal of Scientific Computing 98 (2), 40, 2024 | 8 | 2024 |
| Neural Architecture Search via Bregman Iterations L Bungert, T Roith, D Tenbrinck, M Burger arXiv preprint arXiv:2106.02479, 2021 | 8 | 2021 |
| Variational Graph Methods for Efficient Point Cloud Sparsification D Tenbrinck, F Gaede, M Burger arXiv preprint arXiv:1903.02858, 2019 | 8 | 2019 |
Martin BurgerDeutsches Elektronen-Synchrotron DESY und Universität Hamburguni-hamburg.de üzerinde doğrulanmış e-posta adresine sahip