| Constrained-CNN losses for weakly supervised segmentation H Kervadec, J Dolz, M Tang, E Granger, Y Boykov, IB Ayed Medical Image Analysis 54, 88-99, 2019 | 80 | 2019 |
| Boundary loss for highly unbalanced segmentation H Kervadec, J Bouchtiba, C Desrosiers, É Granger, J Dolz, IB Ayed International Conference on Medical Imaging with Deep Learning, 285-296, 2019 | 64 | 2019 |
| Constrained Deep Networks: Lagrangian Optimization via Log-Barrier Extensions H Kervadec, J Dolz, J Yuan, C Desrosiers, E Granger, IB Ayed arXiv preprint arXiv:1904.04205, 2019 | 13* | 2019 |
| Curriculum semi-supervised segmentation H Kervadec, J Dolz, E Granger, IB Ayed Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019 | 11 | 2019 |
| Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervision H Kervadec, J Dolz, S Wang, E Granger, IB Ayed Medical Imaging with Deep Learning (MIDL), 2020 | 7 | 2020 |
| Constrained domain adaptation for segmentation M Bateson, H Kervadec, J Dolz, H Lombaert, IB Ayed International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 7 | 2019 |
| Polystyrene: The decentralized data shape that never dies S Bouget, H Kervadec, AM Kermarrec, F Taïani 2014 IEEE 34th International Conference on Distributed Computing Systems …, 2014 | 7 | 2014 |
| Discretely-constrained deep network for weakly supervised segmentation J Peng, H Kervadec, J Dolz, IB Ayed, M Pedersoli, C Desrosiers Neural Networks 130, 297-308, 2020 | 6 | 2020 |
| Source-Relaxed Domain Adaptation for Image Segmentation M Bateson, H Kervadec, J Dolz, H Lombaert, IB Ayed arXiv preprint arXiv:2005.03697, 2020 | 1 | 2020 |
| Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need? M Boudiaf, H Kervadec, ZI Masud, P Piantanida, IB Ayed, J Dolz arXiv preprint arXiv:2012.06166, 2020 | | 2020 |
Jose DolzAssistant Professor, ETS Montreal在 etsmtl.ca 的电子邮件经过验证
