Transformers in medical imaging: A survey F Shamshad, S Khan, SW Zamir, MH Khan, M Hayat, FS Khan, H Fu Medical Image Analysis, 102802, 2023 | 466 | 2023 |
Blind image deconvolution using deep generative priors M Asim, F Shamshad, A Ahmed IEEE Transactions on Computational Imaging 6, 1493-1506, 2020 | 121* | 2020 |
A survey on deep reinforcement learning for audio-based applications S Latif, H Cuayáhuitl, F Pervez, F Shamshad, HS Ali, E Cambria Artificial Intelligence Review 56 (3), 2193-2240, 2023 | 63 | 2023 |
Compressed sensing-based robust phase retrieval via deep generative priors F Shamshad, A Ahmed IEEE Sensors Journal 21 (2), 2286-2298, 2020 | 52* | 2020 |
Untrained neural network priors for inverse imaging problems: A survey A Qayyum, I Ilahi, F Shamshad, F Boussaid, M Bennamoun, J Qadir IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (5), 6511-6536, 2022 | 49 | 2022 |
Deep ptych: Subsampled fourier ptychography using generative priors F Shamshad, F Abbas, A Ahmed ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 44 | 2019 |
Transformers in speech processing: A survey S Latif, A Zaidi, H Cuayahuitl, F Shamshad, M Shoukat, J Qadir arXiv preprint arXiv:2303.11607, 2023 | 39 | 2023 |
Towards an adversarially robust normalization approach M Awais, F Shamshad, SH Bae arXiv preprint arXiv:2006.11007, 2020 | 27* | 2020 |
Transformers in medical imaging: A survey. arXiv 2022 F Shamshad, S Khan, SW Zamir, MH Khan, M Hayat, FS Khan, H Fu arXiv preprint arXiv:2201.09873, 0 | 26 | |
Single-shot retinal image enhancement using untrained and pretrained neural networks priors integrated with analytical image priors A Qayyum, W Sultani, F Shamshad, R Tufail, J Qadir Computers in Biology and Medicine 148, 105879, 2022 | 13 | 2022 |
CLIP2Protect: Protecting Facial Privacy using Text-Guided Makeup via Adversarial Latent Search F Shamshad, M Naseer, K Nandakumar Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 10 | 2023 |
Single-shot retinal image enhancement using deep image priors A Qayyum, W Sultani, F Shamshad, J Qadir, R Tufail Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 9 | 2020 |
Adaptive ptych: Leveraging image adaptive generative priors for subsampled fourier ptychography F Shamshad, A Hanif, F Abbas, M Awais, A Ahmed Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 9 | 2019 |
Sparks of large audio models: A survey and outlook S Latif, M Shoukat, F Shamshad, M Usama, H Cuayáhuitl, BW Schuller arXiv preprint arXiv:2308.12792, 2023 | 8 | 2023 |
A survey on deep reinforcement learning for audio-based applications. arXiv 2021 S Latif, H Cuayáhuitl, F Pervez, F Shamshad, HS Ali, E Cambria arXiv preprint arXiv:2101.00240, 0 | 7 | |
Transformers in medical imaging: a survey. 2022 F Shamshad, S Khan, SW Zamir, MH Khan, M Hayat, FS Khan, H Fu arXiv preprint arXiv:2201.09873, 0 | 6 | |
Introducing Data mining for Predicting trends in School Education of Pakistan: Preliminary results and future directions M Asim, F Shamshad, M Awais, A Ahmed Proceedings of the Ninth International Conference on Information and …, 2017 | 5 | 2017 |
Subsampled fourier ptychography using pretrained invertible and untrained network priors F Shamshad, A Hanif, A Ahmed arXiv preprint arXiv:2005.07026, 2020 | 4 | 2020 |
Blind image deconvolution using pretrained generative priors M Asim, F Shamshad, A Ahmed arXiv preprint arXiv:1908.07404, 2019 | 4 | 2019 |
Patchdip exploiting patch redundancy in deep image prior for denoising M Asim, F Shamshad, A Ahmed NeurIPS 2019 Workshop on Solving Inverse Problems with Deep Networks, 2019 | 3 | 2019 |