Shivam Kalra
Cited by
Cited by
Convolutional neural networks for histopathology image classification: Training vs. using pre-trained networks
B Kieffer, M Babaie, S Kalra, HR Tizhoosh
2017 Seventh International Conference on Image Processing Theory, Tools and …, 2017
A comparative study of CNN, BoVW and LBP for classification of histopathological images
MD Kumar, M Babaie, S Zhu, S Kalra, HR Tizhoosh
2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-7, 2017
Comparing LBP, HOG and deep features for classification of histopathology images
TJ Alhindi, S Kalra, KH Ng, A Afrin, HR Tizhoosh
2018 international joint conference on neural networks (IJCNN), 1-7, 2018
Skin lesion segmentation: U-nets versus clustering
BS Lin, K Michael, S Kalra, HR Tizhoosh
2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-7, 2017
Pan-cancer diagnostic consensus through searching archival histopathology images using artificial intelligence
S Kalra, HR Tizhoosh, S Shah, C Choi, S Damaskinos, A Safarpoor, ...
NPJ digital medicine 3 (1), 1-15, 2020
Classification and retrieval of digital pathology scans: A new dataset
M Babaie, S Kalra, A Sriram, C Mitcheltree, S Zhu, A Khatami, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Representation learning of histopathology images using graph neural networks
M Adnan, S Kalra, HR Tizhoosh
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
Yottixel–an image search engine for large archives of histopathology whole slide images
S Kalra, HR Tizhoosh, C Choi, S Shah, P Diamandis, CJV Campbell, ...
Medical Image Analysis 65, 101757, 2020
Fine-tuning and training of densenet for histopathology image representation using tcga diagnostic slides
A Riasatian, M Babaie, D Maleki, S Kalra, M Valipour, S Hemati, M Zaveri, ...
Medical Image Analysis 70, 102032, 2021
Federated learning and differential privacy for medical image analysis
M Adnan, S Kalra, JC Cresswell, GW Taylor, HR Tizhoosh
Scientific reports 12 (1), 1-10, 2022
Automatic classification of pathology reports using TF-IDF Features
S Kalra, L Li, HR Tizhoosh
arXiv preprint arXiv:1903.07406, 2019
Learning permutation invariant representations using memory networks
S Kalra, M Adnan, G Taylor, HR Tizhoosh
European Conference on Computer Vision, 677-693, 2020
Searching images for consensus: can AI remove observer variability in pathology?
HR Tizhoosh, P Diamandis, CJV Campbell, A Safarpoor, S Kalra, ...
The American journal of pathology 191 (10), 1702-1708, 2021
Fuzzy adaptive cruise control system with speed sign detection capability
R Rizvi, S Kalra, C Gosalia, S Rahnamayan
2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 968-976, 2014
Cnn and deep sets for end-to-end whole slide image representation learning
S Hemati, S Kalra, C Meaney, M Babaie, A Ghodsi, H Tizhoosh
Medical Imaging with Deep Learning, 301-311, 2021
A digital pathology solution to resolve the tissue floater conundrum
L Pantanowitz, P Michelow, S Hazelhurst, S Kalra, C Choi, S Shah, ...
Archives of pathology & laboratory medicine 145 (3), 359-364, 2021
Multiple disjoint dictionaries for representation of histopathology images
S Zhu, Y Li, S Kalra, HR Tizhoosh
Journal of Visual Communication and Image Representation 55, 243-252, 2018
Projectron–A shallow and interpretable network for classifying medical images
A Sriram, S Kalra, HR Tizhoosh
2019 International Joint Conference on Neural Networks (IJCNN), 1-9, 2019
Learning opposites using neural networks
S Kalra, A Sriram, S Rahnamayan, HR Tizhoosh
2016 23rd International Conference on Pattern Recognition (ICPR), 1213-1218, 2016
Enhancing clearing-based niching method using delaunay triangulation
S Kalra, S Rahnamayan, K Deb
2017 IEEE Congress on Evolutionary Computation (CEC), 2328-2337, 2017
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