| 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 | 56011 | 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 | 3319 | 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 | 2143 | 2016 |
| Discriminative unsupervised feature learning with convolutional neural networks A Dosovitskiy, JT Springenberg, M Riedmiller, T Brox Advances in neural information processing systems 27, 2014 | 1548 | 2014 |
| Medical image computing and computer-assisted intervention–MICCAI 2015 O Ronneberger, P Fischer, T Brox, N Navab, J Hornegger, WM Wells, ... Cham: Springer, 234-241, 2015 | 1312 | 2015 |
| 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 | 617 | 2015 |
| U-Net: Convolutional networks for biomedical image segmentation. arXiv 2015 O Ronneberger, P Fischer, T Brox arXiv preprint arXiv:1505.04597 2, 2019 | 322 | 2019 |
| Descriptor matching with convolutional neural networks: a comparison to sift P Fischer, A Dosovitskiy, T Brox arXiv preprint arXiv:1405.5769, 2014 | 305 | 2014 |
| 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 | 258 | 2016 |
| 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 | 194 | 2018 |
| Lecture notes in computer science O Ronneberger, P Fischer, T Brox International Conference on Medical Image Computing and Computer-Assisted …, 2015 | 149 | 2015 |
| U-net: Convolutional networks for biomedical image segmentation. CoRR abs/1505.04597 (2015) O Ronneberger, P Fischer, T Brox | 103 | 2015 |
| Image orientation estimation with convolutional networks P Fischer, A Dosovitskiy, T Brox Pattern Recognition: 37th German Conference, GCPR 2015, Aachen, Germany …, 2015 | 83 | 2015 |
| Medical Image Computing and Computer-Assisted Intervention-MICCAI 2015, edited by N O Ronneberger, P Fischer, T Brox Navab, J. Hornegger, WM Wells & AF Frangi, 234-241, 2015 | 78 | 2015 |
| U-Net: convolutional networks for biomedical image segmentation. CoRR, abs/1505.04597 O Ronneberger, P Fischer, T Brox arXiv preprint arXiv:1505.04597, 2015 | 54 | 2015 |
| Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science O Ronneberger, P Fischer, T Brox Springer, 2015 | 51 | 2015 |
| Image descriptors based on curvature histograms P Fischer, T Brox Pattern Recognition: 36th German Conference, GCPR 2014, Münster, Germany …, 2014 | 19 | 2014 |
| myCOMAND automotive user interface: Personalized interaction with multimedia content based on fuzzy preference modeling P Fischer, A Nürnberger User Modeling, Adaptation, and Personalization: 18th International …, 2010 | 9 | 2010 |
| Adaptive and multimodal interaction in the vehicle P Fischer, A Nurnberger 2008 IEEE International Conference on Systems, Man and Cybernetics, 1512-1516, 2008 | 9 | 2008 |
| U-Net: convolutional networks for biomedical image segmentation. May 18, 2015 O Ronneberger, P Fischer, T Brox | 7 | 2018 |
