| A continual learning survey: Defying forgetting in classification tasks M De Lange, R Aljundi, M Masana, S Parisot, X Jia, A Leonardis, ... IEEE transactions on pattern analysis and machine intelligence 44 (7), 3366-3385, 2021 | 2030* | 2021 |
| Disease prediction using graph convolutional networks: application to autism spectrum disorder and Alzheimer’s disease S Parisot, SI Ktena, E Ferrante, M Lee, R Guerrero, B Glocker, D Rueckert Medical image analysis 48, 117-130, 2018 | 593 | 2018 |
| DeepMedic for brain tumor segmentation K Kamnitsas, E Ferrante, S Parisot, C Ledig, AV Nori, A Criminisi, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2016 | 410 | 2016 |
| Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex S Arslan, SI Ktena, A Makropoulos, EC Robinson, D Rueckert, S Parisot NeuroImage 170, 5-30, 2018 | 378 | 2018 |
| Metric learning with spectral graph convolutions on brain connectivity networks SI Ktena, S Parisot, E Ferrante, M Rajchl, M Lee, B Glocker, D Rueckert NeuroImage 169, 431-442, 2018 | 345 | 2018 |
| Learning conditioned graph structures for interpretable visual question answering W Norcliffe-Brown, S Vafeias, S Parisot Advances in neural information processing systems 31, 2018 | 286 | 2018 |
| Spectral graph convolutions for population-based disease prediction S Parisot, SI Ktena, E Ferrante, M Lee, RG Moreno, B Glocker, D Rueckert Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 266 | 2017 |
| Deeplpf: Deep local parametric filters for image enhancement S Moran, P Marza, S McDonagh, S Parisot, G Slabaugh Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 222 | 2020 |
| Distance metric learning using graph convolutional networks: Application to functional brain networks SI Ktena, S Parisot, E Ferrante, M Rajchl, M Lee, B Glocker, D Rueckert Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 219 | 2017 |
| More classifiers, less forgetting: A generic multi-classifier paradigm for incremental learning Y Liu, S Parisot, G Slabaugh, X Jia, A Leonardis, T Tuytelaars Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 106 | 2020 |
| Joint tumor segmentation and dense deformable registration of brain MR images S Parisot, H Duffau, S Chemouny, N Paragios International conference on medical image computing and computer-assisted …, 2012 | 86 | 2012 |
| Concurrent tumor segmentation and registration with uncertainty-based sparse non-uniform graphs S Parisot, W Wells III, S Chemouny, H Duffau, N Paragios Medical image analysis 18 (4), 647-659, 2014 | 66 | 2014 |
| A probabilistic atlas of diffuse WHO grade II glioma locations in the brain S Parisot, A Darlix, C Baumann, S Zouaoui, Y Yordanova, M Blonski, ... PloS one 11 (1), e0144200, 2016 | 59 | 2016 |
| Estimation of intra-operator variability in perfusion parameter measurements using DCE-US M Gauthier, I Leguerney, J Thalmensi, M Chebil, S Parisot, P Peronneau, ... World journal of radiology 3 (3), 70, 2011 | 55 | 2011 |
| A multi-hypothesis approach to color constancy D Hernandez-Juarez, S Parisot, B Busam, A Leonardis, G Slabaugh, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 54 | 2020 |
| Graph-based detection, segmentation & characterization of brain tumors S Parisot, H Duffau, S Chemouny, N Paragios 2012 IEEE Conference on Computer Vision and Pattern Recognition, 988-995, 2012 | 49 | 2012 |
| Group-wise parcellation of the cortex through multi-scale spectral clustering S Parisot, S Arslan, J Passerat-Palmbach, WM Wells III, D Rueckert NeuroImage 136, 68-83, 2016 | 43 | 2016 |
| Low light video enhancement using synthetic data produced with an intermediate domain mapping D Triantafyllidou, S Moran, S McDonagh, S Parisot, G Slabaugh Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 42 | 2020 |
| Clad: A realistic continual learning benchmark for autonomous driving E Verwimp, K Yang, S Parisot, L Hong, S McDonagh, E Pérez-Pellitero, ... Neural Networks 161, 659-669, 2023 | 40 | 2023 |
| Long-tail recognition via compositional knowledge transfer S Parisot, PM Esperança, S McDonagh, TJ Madarasz, Y Yang, Z Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 32 | 2022 |
Daniel RueckertTechnical University of Munich and Imperial College LondonVerified email at tum.de
