| A dataset and a technique for generalized nuclear segmentation for computational pathology N Kumar, R Verma, S Sharma, S Bhargava, A Vahadane, A Sethi IEEE transactions on medical imaging 36 (7), 1550-1560, 2017 | 981 | 2017 |
| Structure-preserving color normalization and sparse stain separation for histological images A Vahadane, T Peng, A Sethi, S Albarqouni, L Wang, M Baust, K Steiger, ... IEEE transactions on medical imaging 35 (8), 1962-1971, 2016 | 786 | 2016 |
| A multi-organ nucleus segmentation challenge N Kumar, R Verma, D Anand, Y Zhou, OF Onder, E Tsougenis, H Chen, ... IEEE transactions on medical imaging 39 (5), 1380-1391, 2019 | 453 | 2019 |
| Drowsy driver detection using representation learning K Dwivedi, K Biswaranjan, A Sethi 2014 IEEE international advance computing conference (IACC), 995-999, 2014 | 249 | 2014 |
| Classification of breast cancer histology using deep learning A Golatkar, D Anand, A Sethi Image Analysis and Recognition: 15th International Conference, ICIAR 2018 …, 2018 | 166 | 2018 |
| MoNuSAC2020: A multi-organ nuclei segmentation and classification challenge R Verma, N Kumar, A Patil, NC Kurian, S Rane, S Graham, QD Vu, ... IEEE Transactions on Medical Imaging 40 (12), 3413-3423, 2021 | 149 | 2021 |
| A detection-based multiple object tracking method M Han, A Sethi, W Hua, Y Gong 2004 International Conference on Image Processing, 2004. ICIP'04. 5, 3065-3068, 2004 | 118 | 2004 |
| The importance of information localization in scene gist recognition. LC Loschky, A Sethi, DJ Simons, TN Pydimarri, D Ochs, JL Corbeille Journal of Experimental Psychology: Human Perception and Performance 33 (6 …, 2007 | 101 | 2007 |
| Histographs: graphs in histopathology D Anand, S Gadiya, A Sethi Medical Imaging 2020: Digital Pathology 11320, 150-155, 2020 | 79* | 2020 |
| A learnable distortion correction module for modulation recognition K Yashashwi, A Sethi, P Chaporkar IEEE Wireless Communications Letters 8 (1), 77-80, 2018 | 77 | 2018 |
| Empirical comparison of color normalization methods for epithelial-stromal classification in H and E images A Sethi, L Sha, AR Vahadane, RJ Deaton, N Kumar, V Macias, PH Gann Journal of pathology informatics 7 (1), 17, 2016 | 68 | 2016 |
| Systems and methods for computational pathology using points-of-interest A Sethi, N Kumar US Patent 10,573,003, 2020 | 62 | 2020 |
| Convolutional neural networks for prostate cancer recurrence prediction N Kumar, R Verma, A Arora, A Kumar, S Gupta, A Sethi, PH Gann Medical Imaging 2017: Digital Pathology 10140, 106-117, 2017 | 61 | 2017 |
| Convolutional neural networks for wavelet domain super resolution N Kumar, R Verma, A Sethi Pattern Recognition Letters 90, 65-71, 2017 | 60 | 2017 |
| The role of higher order image statistics in masking scene gist recognition LC Loschky, BC Hansen, A Sethi, TN Pydimarri Attention, Perception, & Psychophysics 72, 427-444, 2010 | 60 | 2010 |
| Fast learning-based single image super-resolution N Kumar, A Sethi IEEE Transactions on Multimedia 18 (8), 1504-1515, 2016 | 52 | 2016 |
| Deep learning to estimate human epidermal growth factor receptor 2 status from hematoxylin and eosin-stained breast tissue images D Anand, NC Kurian, S Dhage, N Kumar, S Rane, PH Gann, A Sethi Journal of pathology informatics 11 (1), 19, 2020 | 51 | 2020 |
| Curve and surface duals and the recognition of curved 3D objects from their silhouettes A Sethi, D Renaudie, D Kriegman, J Ponce International journal of computer vision 58, 73-86, 2004 | 50 | 2004 |
| Weakly supervised learning on unannotated H&E‐stained slides predicts BRAF mutation in thyroid cancer with high accuracy D Anand, K Yashashwi, N Kumar, S Rane, PH Gann, A Sethi The Journal of pathology 255 (3), 232-242, 2021 | 46 | 2021 |
| Hyperspectral tissue image segmentation using semi-supervised NMF and hierarchical clustering N Kumar, P Uppala, K Duddu, H Sreedhar, V Varma, G Guzman, M Walsh, ... IEEE transactions on medical imaging 38 (5), 1304-1313, 2018 | 45 | 2018 |
Neeraj KumarMemorial Sloan Kettering Cancer CenterEmail verificata su iitg.ernet.in
