| The Visual Object Tracking VOT2013 challenge results M Kristan, R Pflugfelder, A Leonardis, J Matas, F Porikli, A Khajenezhad, ... IEEE International Conference on Computer Vision Workshops, 98-111, 2013 | 2159 | 2013 |
| Image super-resolution using progressive generative adversarial networks for medical image analysis D Mahapatra, B Bozorgtabar, R Garnavi Computerized Medical Imaging and Graphics 71, 30-39, 2019 | 277 | 2019 |
| Efficient active learning for image classification and segmentation using a sample selection and conditional generative adversarial network D Mahapatra, B Bozorgtabar, JP Thiran, M Reyes International Conference on Medical Image Computing and Computer-Assisted …, 2018 | 204 | 2018 |
| An improved signal segmentation using moving average and Savitzky-Golay filter H Azami, K Mohammadi, B Bozorgtabar Scientific Research Publishing, 2012 | 199 | 2012 |
| Srobb: Targeted perceptual loss for single image super-resolution MS Rad, B Bozorgtabar, UV Marti, M Basler, HK Ekenel, JP Thiran Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 167 | 2019 |
| Image super resolution using generative adversarial networks and local saliency maps for retinal image analysis D Mahapatra, B Bozorgtabar, S Hewavitharanage, R Garnavi Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 112 | 2017 |
| Quantifying explainers of graph neural networks in computational pathology G Jaume, P Pati, B Bozorgtabar, A Foncubierta, AM Anniciello, F Feroce, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 98 | 2021 |
| Self-attentive spatial adaptive normalization for cross-modality domain adaptation D Tomar, M Lortkipanidze, G Vray, B Bozorgtabar, JP Thiran IEEE transactions on medical imaging 40 (10), 2926-2938, 2021 | 73 | 2021 |
| Divide-and-rule: self-supervised learning for survival analysis in colorectal cancer C Abbet, I Zlobec, B Bozorgtabar, JP Thiran Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 63 | 2020 |
| Exploiting local and generic features for accurate skin lesions classification using clinical and dermoscopy imaging Z Ge, S Demyanov, B Bozorgtabar, M Abedini, R Chakravorty, A Bowling, ... 2017 IEEE 14th international symposium on biomedical imaging (ISBI 2017 …, 2017 | 63 | 2017 |
| Sparse coding based skin lesion segmentation using dynamic rule-based refinement B Bozorgtabar, M Abedini, R Garnavi Machine Learning in Medical Imaging: 7th International Workshop, MLMI 2016 …, 2016 | 63 | 2016 |
| Skin lesion segmentation using deep convolution networks guided by local unsupervised learning B Bozorgtabar, S Sedai, PK Roy, R Garnavi IBM Journal of Research and Development 61 (4/5), 6: 1-6: 8, 2017 | 59 | 2017 |
| Structure preserving stain normalization of histopathology images using self supervised semantic guidance D Mahapatra, B Bozorgtabar, JP Thiran, L Shao Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 57 | 2020 |
| DermoNet: densely linked convolutional neural network for efficient skin lesion segmentation S Baghersalimi, B Bozorgtabar, P Schmid-Saugeon, HK Ekenel, ... EURASIP Journal on Image and Video Processing 2019 (1), 71, 2019 | 54 | 2019 |
| Retinal vasculature segmentation using local saliency maps and generative adversarial networks for image super resolution D Mahapatra, B Bozorgtabar arXiv preprint arXiv:1710.04783, 2017 | 53 | 2017 |
| ExprADA: Adversarial domain adaptation for facial expression analysis B Bozorgtabar, D Mahapatra, JP Thiran Pattern Recognition 100, 107111, 2020 | 52 | 2020 |
| Learning whole-slide segmentation from inexact and incomplete labels using tissue graphs V Anklin, P Pati, G Jaume, B Bozorgtabar, A Foncubierta-Rodriguez, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 51 | 2021 |
| Salad: Self-supervised aggregation learning for anomaly detection on x-rays B Bozorgtabar, D Mahapatra, G Vray, JP Thiran Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 51 | 2020 |
| Syndemo: Synergistic deep feature alignment for joint learning of depth and ego-motion B Bozorgtabar, MS Rad, D Mahapatra, JP Thiran Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 47 | 2019 |
| Scorenet: Learning non-uniform attention and augmentation for transformer-based histopathological image classification T Stegmüller, B Bozorgtabar, A Spahr, JP Thiran Proceedings of the IEEE/CVF winter Conference on applications of computer …, 2023 | 43 | 2023 |
Jean-Philippe ThiranEcole Polytechnique Fédérale de Lausanne (EPFL)Verified email at epfl.ch