| CERES: a new cerebellum lobule segmentation method JE Romero, P Coupé, R Giraud, VT Ta, V Fonov, MTM Park, ... Neuroimage 147, 916-924, 2017 | 146 | 2017 |
| AssemblyNet: A large ensemble of CNNs for 3D whole brain MRI segmentation P Coupé, B Mansencal, M Clément, R Giraud, BD de Senneville, VT Ta, ... NeuroImage 219, 117026, 2020 | 85 | 2020 |
| An optimized patchmatch for multi-scale and multi-feature label fusion R Giraud, VT Ta, N Papadakis, JV Manjón, DL Collins, P Coupé, ... NeuroImage 124, 770-782, 2016 | 83 | 2016 |
| Optimized patchmatch for near real time and accurate label fusion VT Ta, R Giraud, DL Collins, P Coupé Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014 | 59 | 2014 |
| Robust superpixels using color and contour features along linear path R Giraud, VT Ta, N Papadakis Computer Vision and Image Understanding 170, 1-13, 2018 | 50 | 2018 |
| SuperPatchMatch: An algorithm for robust correspondences using superpixel patches R Giraud, VT Ta, A Bugeau, P Coupé, N Papadakis | 46 | 2017 |
| AssemblyNet: a novel deep decision-making process for whole brain MRI segmentation P Coupé, B Mansencal, M Clément, R Giraud, BD de Senneville, VT Ta, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 26 | 2019 |
| Evaluation framework of superpixel methods with a global regularity measure R Giraud, VT Ta, N Papadakis Journal of Electronic Imaging 26 (6), 061603-061603, 2017 | 25 | 2017 |
| SCALP: Superpixels with contour adherence using linear path R Giraud, VT Ta, N Papadakis 2016 23rd International Conference on Pattern Recognition (ICPR), 2374-2379, 2016 | 20 | 2016 |
| Superpixel-based color transfer R Giraud, VT Ta, N Papadakis 2017 IEEE International Conference on Image Processing (ICIP), 700-704, 2017 | 10 | 2017 |
| Texture-aware superpixel segmentation R Giraud, VT Ta, N Papadakis, Y Berthoumieu 2019 IEEE International Conference on Image Processing (ICIP), 1465-1469, 2019 | 9 | 2019 |
| Robust shape regularity criteria for superpixel evaluation R Giraud, VT Ta, N Papadakis 2017 IEEE International Conference on Image Processing (ICIP), 3455-3459, 2017 | 8 | 2017 |
| Texture superpixel clustering from patch-based nearest neighbor matching R Giraud, Y Berthoumieu 2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019 | 6 | 2019 |
| Patch-based DTI grading: Application to Alzheimer’s disease classification K Hett, VT Ta, R Giraud, M Mondino, JV Manjón, P Coupé, ... Patch-Based Techniques in Medical Imaging: Second International Workshop …, 2016 | 6 | 2016 |
| Analysis of different losses for deep learning image colorization C Ballester, A Bugeau, H Carrillo, M Clément, R Giraud, L Raad, P Vitoria arXiv preprint arXiv:2204.02980, 2022 | 3 | 2022 |
| Influence of Color Spaces for Deep Learning Image Colorization C Ballester, A Bugeau, H Carrillo, M Clément, R Giraud, L Raad, P Vitoria arXiv preprint arXiv:2204.02850, 2022 | 3 | 2022 |
| Generalized shortest path-based superpixels for accurate segmentation of spherical images R Giraud, RB Pinheiro, Y Berthoumieu 2020 25th International Conference on Pattern Recognition (ICPR), 2650-2656, 2021 | 3 | 2021 |
| Multi-scale superpatch matching using dual superpixel descriptors R Giraud, M Boyer, M Clément Pattern Recognition Letters 133, 129-136, 2020 | 3 | 2020 |
| Patch-Based abnormality maps for improved deep learning-based classification of Huntington’s disease K Hett, R Giraud, H Johnson, JS Paulsen, JD Long, I Oguz Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 2 | 2020 |
| Algorithmes de correspondance et superpixels pour l’analyse et le traitement d’images R Giraud Université de Bordeaux, 2017 | 2 | 2017 |
Vinh-Thong TAMaître de conférence, Bordeaux INP Aquitaine/ENSEIRB-MATMECAAdresse e-mail validée de labri.fr
