| Supervised feature learning for curvilinear structure segmentation C Becker, R Rigamonti, V Lepetit, P Fua Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013 | 196 | 2013 |
| Classification of aerial photogrammetric 3D point clouds C Becker, E Rosinskaya, N Häni, E D'Angelo, C Strecha Photogrammetric Engineering & Remote Sensing 84 (5), 287-295, 2018 | 75 | 2018 |
| Network flow integer programming to track elliptical cells in time-lapse sequences E Türetken, X Wang, CJ Becker, C Haubold, P Fua IEEE transactions on medical imaging 36 (4), 942-951, 2016 | 74 | 2016 |
| Learning context cues for synapse segmentation C Becker, K Ali, G Knott, P Fua IEEE transactions on medical imaging 32 (10), 1864-1877, 2013 | 74 | 2013 |
| Fast part-based classification for instrument detection in minimally invasive surgery R Sznitman, C Becker, P Fua Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014 | 73 | 2014 |
| The effects of aging on neuropil structure in mouse somatosensory cortex—A 3D electron microscopy analysis of layer 1 C Cali, M Wawrzyniak, C Becker, B Maco, M Cantoni, A Jorstad, B Nigro, ... PloS one 13 (7), e0198131, 2018 | 63 | 2018 |
| Classification of aerial photogrammetric 3D point clouds C Becker, N Häni, E Rosinskaya, E d'Angelo, C Strecha arXiv preprint arXiv:1705.08374, 2017 | 54 | 2017 |
| Non-linear domain adaptation with boosting CJ Becker, CM Christoudias, P Fua Advances in neural information processing systems 26, 2013 | 49 | 2013 |
| Learning structured models for segmentation of 2-D and 3-D imagery A Lucchi, P Márquez-Neila, C Becker, Y Li, K Smith, G Knott, P Fua IEEE transactions on medical imaging 34 (5), 1096-1110, 2014 | 47 | 2014 |
| Detecting irregular curvilinear structures in gray scale and color imagery using multi-directional oriented flux E Turetken, C Becker, P Glowacki, F Benmansour, P Fua Proceedings of the IEEE International Conference on Computer Vision, 1553-1560, 2013 | 47 | 2013 |
| Learning context cues for synapse segmentation in EM volumes C Becker, K Ali, G Knott, P Fua Medical Image Computing and Computer-Assisted Intervention–MICCAI 2012: 15th …, 2012 | 37 | 2012 |
| Domain adaptation for microscopy imaging C Becker, CM Christoudias, P Fua IEEE Transactions on Medical Imaging 34 (5), 1125-1139, 2014 | 36 | 2014 |
| Exploiting enclosing membranes and contextual cues for mitochondria segmentation A Lucchi, C Becker, P Márquez Neila, P Fua Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014 | 33 | 2014 |
| Fast object detection with entropy-driven evaluation R Sznitman, C Becker, F Fleuret, P Fua Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 30 | 2013 |
| Scalable unsupervised domain adaptation for electron microscopy R Bermúdez-Chacón, C Becker, M Salzmann, P Fua Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 26 | 2016 |
| Simultaneous sonar beacon localization & AUV navigation C Becker, D Ribas, P Ridao IFAC Proceedings Volumes 45 (27), 200-205, 2012 | 18 | 2012 |
| Visual correspondences for unsupervised domain adaptation on electron microscopy images R Bermúdez-Chacón, O Altingoevde, C Becker, M Salzmann, P Fua IEEE transactions on medical imaging 39 (4), 1256-1267, 2019 | 13 | 2019 |
| Transfer learning by sharing support vectors VH Ablavsky, CJ Becker, P Fua | 10 | 2012 |
| Globally optimal cell tracking using integer programming E Türetken, X Wang, C Becker, C Haubold, P Fua arXiv preprint arXiv:1501.05499, 2015 | 9 | 2015 |
| Kernelboost: Supervised learning of image features for classification CJ Becker, R Rigamonti, V Lepetit, P Fua | 9 | 2013 |
Pascal FuaProfessor Computer Science, EPFLVerified email at epfl.ch
