| Transformers in vision: A survey S Khan, M Naseer, M Hayat, SW Zamir, FS Khan, M Shah ACM computing surveys (CSUR) 54 (10s), 1-41, 2022 | 2722 | 2022 |
| Restormer: Efficient transformer for high-resolution image restoration SW Zamir, A Arora, S Khan, M Hayat, FS Khan, MH Yang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 2382 | 2022 |
| Multi-stage progressive image restoration SW Zamir, A Arora, S Khan, M Hayat, FS Khan, MH Yang, L Shao Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 1766 | 2021 |
| Cost-sensitive learning of deep feature representations from imbalanced data SH Khan, M Hayat, M Bennamoun, FA Sohel, R Togneri IEEE transactions on neural networks and learning systems 29 (8), 3573-3587, 2017 | 1112 | 2017 |
| Learning enriched features for real image restoration and enhancement SW Zamir, A Arora, S Khan, M Hayat, FS Khan, MH Yang, L Shao Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 786 | 2020 |
| Transformers in medical imaging: A survey F Shamshad, S Khan, SW Zamir, MH Khan, M Hayat, FS Khan, H Fu Medical Image Analysis 88, 102802, 2023 | 665 | 2023 |
| Intriguing properties of vision transformers MM Naseer, K Ranasinghe, SH Khan, M Hayat, F Shahbaz Khan, ... Advances in Neural Information Processing Systems 34, 23296-23308, 2021 | 654 | 2021 |
| Cycleisp: Real image restoration via improved data synthesis SW Zamir, A Arora, S Khan, M Hayat, FS Khan, MH Yang, L Shao Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 397 | 2020 |
| Learning enriched features for fast image restoration and enhancement SW Zamir, A Arora, S Khan, M Hayat, FS Khan, MH Yang, L Shao IEEE transactions on pattern analysis and machine intelligence 45 (2), 1934-1948, 2022 | 293 | 2022 |
| A self-supervised approach for adversarial robustness M Naseer, S Khan, M Hayat, FS Khan, F Porikli Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 292 | 2020 |
| Random path selection for continual learning J Rajasegaran, M Hayat, SH Khan, FS Khan, L Shao Advances in neural information processing systems 32, 2019 | 257 | 2019 |
| Striking the right balance with uncertainty S Khan, M Hayat, SW Zamir, J Shen, L Shao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 219 | 2019 |
| Deep reconstruction models for image set classification M Hayat, M Bennamoun, S An IEEE transactions on pattern analysis and machine intelligence 37 (4), 713-727, 2014 | 200 | 2014 |
| A robust volumetric transformer for accurate 3D tumor segmentation H Peiris, M Hayat, Z Chen, G Egan, M Harandi International conference on medical image computing and computer-assisted …, 2022 | 197 | 2022 |
| Image super-resolution as a defense against adversarial attacks A Mustafa, SH Khan, M Hayat, J Shen, L Shao IEEE Transactions on Image Processing 29, 1711-1724, 2019 | 197 | 2019 |
| itaml: An incremental task-agnostic meta-learning approach J Rajasegaran, S Khan, M Hayat, FS Khan, M Shah Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 188 | 2020 |
| Adversarial defense by restricting the hidden space of deep neural networks A Mustafa, S Khan, M Hayat, R Goecke, J Shen, L Shao Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 184 | 2019 |
| An efficient 3D face recognition approach using local geometrical signatures Y Lei, M Bennamoun, M Hayat, Y Guo Pattern recognition 47 (2), 509-524, 2014 | 155 | 2014 |
| NTIRE 2023 challenge on efficient super-resolution: Methods and results Y Li, Y Zhang, R Timofte, L Van Gool, L Yu, Y Li, X Li, T Jiang, Q Wu, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 137 | 2023 |
| Regularization of deep neural networks with spectral dropout SH Khan, M Hayat, F Porikli Neural Networks 110, 82-90, 2019 | 133 | 2019 |
Salman KhanMBZUAI, Australian National University在 anu.edu.au 的电子邮件经过验证
