| Multiple Instance Learning: A Survey of Problem Characteristics and Applications MA Carbonneau, V Cheplygina, E Granger, G Gagnon Pattern Recognition 77, 329-353, 2018 | 373 | 2018 |
| Boundary loss for highly unbalanced segmentation H Kervadec, J Bouchtiba, C Desrosiers, E Granger, J Dolz, I Ben Ayed Medical Image Analysis 67, 2021 | 239 | 2021 |
| Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses J Rony, LG Hafemann, LS Oliveira, I Ben Ayed, R Sabourin, E Granger CVPR 2019: IEEE Conference on Computer Vision and Pattern Recognition, Long …, 2019 | 203 | 2019 |
| 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 | 183 | 2019 |
| A what-and-where fusion neural network for recognition and tracking of multiple radar emitters E Granger, M Rubin, S Grossberg, P Lavoie Neural Networks 14 (3), 325-344, 2001 | 150 | 2001 |
| An adaptive classification system for video-based face recognition JF Connolly, E Granger, R Sabourin Information Sciences 192, 50-70, 2012 | 131 | 2012 |
| Iterative Boolean combination of classifiers in the ROC space: An application to anomaly detection with HMMs W Khreich, E Granger, A Miri, R Sabourin Pattern Recognition 43 (8), 2732-2752, 2010 | 131 | 2010 |
| A survey of techniques for incremental learning of HMM parameters W Khreich, E Granger, A Miri, R Sabourin Information Sciences 197, 105-130, 2012 | 130 | 2012 |
| Multi-feature extraction and selection in writer-independent off-line signature verification D Rivard, E Granger, R Sabourin International Journal on Document Analysis and Recognition (IJDAR) 16 (1 …, 2013 | 110 | 2013 |
| Dynamic selection of generative–discriminative ensembles for off-line signature verification L Batista, E Granger, R Sabourin Pattern Recognition 45 (4), 1326-1340, 2012 | 109 | 2012 |
| Optics for high-performance servers and supercomputers AF Benner, DM Kuchta, PK Pepeljugoski, RA Budd, G Hougham, ... 2010 Conference on Optical Fiber Communication (OFC/NFOEC), collocated …, 2010 | 97 | 2010 |
| Hybrid writer‐independent–writer‐dependent offline signature verification system GS Eskander, R Sabourin, E Granger IET biometrics 2 (4), 169-181, 2013 | 91 | 2013 |
| Laplacian Regularized Few-Shot Learning IM Ziko, J Dolz, E Granger, I Ben Ayed ICML 2020: Int'l Conference on Machine Learning, Vienna, Austria, 2020 | 77 | 2020 |
| Partially-supervised learning from facial trajectories for face recognition in video surveillance M De-la-Torre, E Granger, PVW Radtke, R Sabourin, DO Gorodnichy Information Fusion 24, 31–53, 2015 | 76 | 2015 |
| Adaptive appearance model tracking for still-to-video face recognition MAA Dewan, E Granger, GL Marcialis, R Sabourin, F Roli Pattern Recognition 49, 129–151, 2016 | 73 | 2016 |
| Adaptive ROC-based ensembles of HMMs applied to anomaly detection W Khreich, E Granger, A Miri, R Sabourin Pattern Recognition 45 (1), 208-230, 2012 | 71 | 2012 |
| Unsupervised Domain Adaptation in the Dissimilarity Space for Person Re-identification D Mekhazni, A Bhuiyan, G Ekladious, E Granger ECCV 2020: European Conf. on Computer Vision, Glasgow, UK., 2020 | 66 | 2020 |
| On the memory complexity of the forward–backward algorithm W Khreich, E Granger, A Miri, R Sabourin Pattern Recognition Letters 31 (2), 91-99, 2010 | 62 | 2010 |
| Multi-region segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks J Dolz, X Xu, J Rony, J Yuan, Y Liu, E Granger, C Desrosiers, X Zhang, ... Medical Physics, DOI: 10.1002/mp.13240, 2018 | 60 | 2018 |
| Dynamic Ensembles of Exemplar-SVMs for Still-to-Video Face Recognition S Bashbaghi, E Granger, R Sabourin, GA Bilodeau Pattern Recognition 69, 61-81, 2017 | 59 | 2017 |
Robert SabourinProfessor emeritus @ École de technologie supérieure - LIVIA - REPARTIVerified email at etsmtl.ca
