| U-net: Convolutional networks for biomedical image segmentation O Ronneberger, P Fischer, T Brox Medical image computing and computer-assisted intervention–MICCAI 2015: 18th …, 2015 | 106293 | 2015 |
| Flownet: Learning optical flow with convolutional networks A Dosovitskiy, P Fischer, E Ilg, P Hausser, C Hazirbas, V Golkov, ... Proceedings of the IEEE international conference on computer vision, 2758-2766, 2015 | 4760 | 2015 |
| A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation N Mayer, E Ilg, P Hausser, P Fischer, D Cremers, A Dosovitskiy, T Brox Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 3319 | 2016 |
| Medical image computing and computer-assisted intervention–MICCAI 2015 O Ronneberger, P Fischer, T Brox, N Navab, J Hornegger, WM Wells, ... Proceedings of the 18th International Conference, Munich, Germany, 5-9, 2015 | 2755* | 2015 |
| Discriminative unsupervised feature learning with convolutional neural networks A Dosovitskiy, JT Springenberg, M Riedmiller, T Brox Advances in neural information processing systems 27, 2014 | 2035 | 2014 |
| Flownet: Learning optical flow with convolutional networks P Fischer, A Dosovitskiy, E Ilg, P Häusser, C Hazırbaş, V Golkov, ... arXiv preprint arXiv:1504.06852, 2015 | 750 | 2015 |
| U-Net: Convolutional networks for biomedical image segmentation. arXiv 2015 O Ronneberger, P Fischer, T Brox arXiv preprint arXiv:1505.04597, 2015 | 705 | 2015 |
| U-net: Convolutional networks for biomedical image segmentation P Fischer, T Brox International Conference on Medical image computing and computer-assisted …, 2015 | 497 | 2015 |
| A benchmark for comparison of dental radiography analysis algorithms CW Wang, CT Huang, JH Lee, CH Li, SW Chang, MJ Siao, TM Lai, ... Medical image analysis 31, 63-76, 2016 | 402 | 2016 |
| Descriptor matching with convolutional neural networks: a comparison to sift P Fischer, A Dosovitskiy, T Brox arXiv preprint arXiv:1405.5769, 2014 | 334 | 2014 |
| Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015, Lecture Notes in Computer Science O Ronneberger, P Fischer, T Brox, N Navab, J Hornegger, WM Wells, ... Chapter 28, 234-241, 2015 | 320 | 2015 |
| What makes good synthetic training data for learning disparity and optical flow estimation? N Mayer, E Ilg, P Fischer, C Hazirbas, D Cremers, A Dosovitskiy, T Brox International Journal of Computer Vision 126, 942-960, 2018 | 252 | 2018 |
| U-net: Convolutional networks for biomedical image segmentation. CoRR abs/1505.04597 (2015) O Ronneberger, P Fischer, T Brox | 167 | 2015 |
| Medical Image Computing and Computer-Assisted Intervention—MICCAI 2015, Proceedings of the 18th International Conference, Munich, Germany, 5–9 October 2015 O Ronneberger, P Fischer, T Brox Proceedings, Part III 18, 2015 | 111 | 2015 |
| Image orientation estimation with convolutional networks P Fischer, A Dosovitskiy, T Brox Pattern Recognition: 37th German Conference, GCPR 2015, Aachen, Germany …, 2015 | 106 | 2015 |
| MICCAI 2015. LNCS O Ronneberger, P Fischer, T Brox, N Navab, J Hornegger, WM Wells, ... Springer, 2015 | 85 | 2015 |
| Discriminative unsupervised feature learning with exemplar convolutional neural networks D Alexey, P Fischer, J Tobias, MR Springenberg, T Brox IEEE TPAMI 38 (9), 1734-1747, 2016 | 80 | 2016 |
| Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) O Ronneberger, P Fischer, T Brox Springer 9351, 234-41, 2015 | 69 | 2015 |
| U-net: Convolutional networks for 420 biomedical image segmentation O Ronneberger, P Fischer, T Brox CoRR, abs/1505.04597 421, 2015 | 67 | 2015 |
| Dental X-ray image segmentation using a U-shaped Deep Convolutional network O Ronneberger, P Fischer, T Brox International Symposium on Biomedical Imaging 1, 1-13, 2015 | 59 | 2015 |
