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Neeraj Kumar
Neeraj Kumar
Research Associate, Computing Science, University of Alberta
Verified email at iitg.ernet.in - Homepage
Title
Cited by
Cited by
Year
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
4652017
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
1302019
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
542016
Fast learning-based single image super-resolution
N Kumar, A Sethi
IEEE Transactions on Multimedia 18 (8), 1504-1515, 2016
432016
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
422017
Convolutional neural networks for wavelet domain super resolution
N Kumar, R Verma, A Sethi
Pattern Recognition Letters 90, 65-71, 2017
412017
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
272021
Systems and methods for computational pathology using points-of-interest
A Sethi, N Kumar
US Patent 10,573,003, 2020
222020
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
182018
Multi-organ nuclei segmentation and classification challenge 2020
R Verma, N Kumar, A Patil, NC Kurian, S Rane, A Sethi
IEEE transactions on medical imaging 39 (1380-1391), 8, 2020
162020
Detecting multiple sub-types of breast cancer in a single patient
ASPHG Ruchika Verma, Neeraj Kumar
IEEE International Conference on Image Processing (ICIP), 2016
152016
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
132020
Neural network based image deblurring
N Kumar, R Nallamothu, A Sethi
11th Symposium on Neural Network Applications in Electrical Engineering, 219-222, 2012
132012
Learning to predict super resolution wavelet coefficients
N Kumar, NK Rai, A Sethi
Proceedings of the 21st International Conference on Pattern Recognition …, 2012
122012
Neural network based single image super resolution
N Kumar, PK Deswal, J Mehta, A Sethi
11th Symposium on Neural Network Applications in Electrical Engineering, 213-218, 2012
112012
Quantification of intrinsic subtype ambiguity in Luminal A breast cancer and its relationship to clinical outcomes
N Kumar, D Zhao, D Bhaumik, PH Sethi, Amit and Gann
BMC Cancer 19 (215), 2019
92019
A spatial neighbourhood based learning setup for super resolution
A Sethi, N Kumar, NK Rai
2012 Annual IEEE India Conference (INDICON), 790-793, 2012
72012
Learning based super-resolution of histological images
A Vahadane, N Kumar, A Sethi
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 816-819, 2016
62016
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
52021
Super resolution by comprehensively exploiting dependencies of wavelet coefficients
N Kumar, A Sethi
IEEE Transactions on Multimedia 20 (2), 298-309, 2017
52017
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