| MoDL: Model Based Deep Learning Architecture for Inverse Problems HK Aggarwal, MP Mani, M Jacob IEEE Transactions on Medical Imaging 38 (2), 394-405, 2019 | 1024 | 2019 |
| Hyperspectral Image Denoising Using Spatio-Spectral Total Variation HK Aggarwal, A Majumdar IEEE Geoscience and Remote Sensing Letters 13 (3), 442-446, 2016 | 237 | 2016 |
| Dynamic MRI using model‐based deep learning and SToRM priors: MoDL‐SToRM S Biswas, HK Aggarwal, M Jacob Magnetic resonance in medicine 82 (1), 485-494, 2019 | 92 | 2019 |
| J-MoDL: Joint Model-Based Deep Learning for Optimized Sampling and Reconstruction HK Aggarwal, M Jacob IEEE Journal of Selected Topics in Signal Processing 14 (6), 1-12, 2020 | 83 | 2020 |
| Hyperspectral Unmixing in the Presence of Mixed Noise Using Joint-Sparsity and Total Variation HK Aggarwal, A Majumdar IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016 | 60 | 2016 |
| Discriminative robust deep dictionary learning for hyperspectral image classification V Singhal, HK Aggarwal, S Tariyal, A Majumdar IEEE Transactions on Geoscience and Remote Sensing 55 (9), 5274-5283, 2017 | 55 | 2017 |
| Deep generalization of structured low-rank algorithms (Deep-SLR) A Pramanik, HK Aggarwal, M Jacob IEEE transactions on medical imaging 39 (12), 4186-4197, 2020 | 53 | 2020 |
| MoDL-MUSSELS: model-based deep learning for multishot sensitivity-encoded diffusion MRI HK Aggarwal, MP Mani, M Jacob IEEE transactions on medical imaging 39 (4), 1268-1277, 2019 | 46 | 2019 |
| Compressive sensing multi-spectral demosaicing from single sensor architecture HK Aggarwal, A Majumdar 2014 IEEE China Summit & International Conference on Signal and Information …, 2014 | 39 | 2014 |
| Single-sensor multi-spectral image demosaicing algorithm using learned interpolation weights HK Aggarwal, A Majumdar 2014 IEEE Geoscience and Remote Sensing Symposium, 2011-2014, 2014 | 36 | 2014 |
| Model based image reconstruction using deep learned priors (MODL) HK Aggarwal, MP Mani, M Jacob 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 29 | 2018 |
| Impulse denoising for hyper-spectral images: A blind compressed sensing approach A Majumdar, N Ansari, H Aggarwal, P Biyani Signal Processing 119, 136-141, 2016 | 29 | 2016 |
| Mixed Gaussian and impulse denoising of hyperspectral images HK Aggarwal, A Majumdar 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2015 | 27 | 2015 |
| Exploiting spatiospectral correlation for impulse denoising in hyperspectral images HK Aggarwal, A Majumdar Journal of Electronic Imaging 24 (1), 013027-013027, 2015 | 26 | 2015 |
| Improved MUSSELS reconstruction for high‐resolution multi‐shot diffusion weighted imaging M Mani, HK Aggarwal, V Magnotta, M Jacob Magnetic resonance in medicine 83 (6), 2253-2263, 2020 | 23 | 2020 |
| Model-based deep learning for reconstruction of joint kq under-sampled high resolution diffusion MRI MP Mani, HK Aggarwal, S Ghosh, M Jacob 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 913-916, 2020 | 20 | 2020 |
| Generalized synthesis and analysis prior algorithms with application to impulse denoising HK Aggarwal, A Majumdar Proceedings of the 2014 Indian Conference on Computer Vision Graphics and …, 2014 | 19 | 2014 |
| Label-consistent transform learning for hyperspectral image classification J Maggu, HK Aggarwal, A Majumdar IEEE Geoscience and Remote Sensing Letters 16 (9), 1502-1506, 2019 | 18 | 2019 |
| Ensure: Ensemble Stein’s unbiased risk estimator for unsupervised learning HK Aggarwal, A Pramanik, M Jacob ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 17 | 2021 |
| Multi-spectral demosaicing technique for single-sensor imaging HK Aggarwal, A Majumdar 2013 Fourth National Conference on Computer Vision, Pattern Recognition …, 2013 | 16 | 2013 |
Mathews JacobUniversity of IowaVerificeret mail på uiowa.edu
