| 2017 robotic instrument segmentation challenge M Allan, A Shvets, T Kurmann, Z Zhang, R Duggal, YH Su, N Rieke, ... arXiv preprint arXiv:1902.06426, 2019 | 130* | 2019 |
| SD-layer: stain deconvolutional layer for CNNs in medical microscopic imaging R Duggal, A Gupta, R Gupta, P Mallick Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 81 | 2017 |
| Overlapping cell nuclei segmentation in microscopic images using deep belief networks R Duggal, A Gupta, R Gupta, M Wadhwa, C Ahuja Proceedings of the tenth Indian conference on computer vision, graphics and …, 2016 | 72 | 2016 |
| GCTI-SN: Geometry-inspired chemical and tissue invariant stain normalization of microscopic medical images A Gupta, R Duggal, S Gehlot, R Gupta, A Mangal, L Kumar, N Thakkar, ... Medical Image Analysis 65, 101788, 2020 | 64 | 2020 |
| Stain color normalization and segmentation of plasma cells in microscopic images as a prelude to development of computer assisted automated disease diagnostic tool in multiple … R Gupta, P Mallick, R Duggal, A Gupta, O Sharma Clinical Lymphoma, Myeloma and Leukemia 17 (1), e99, 2017 | 58 | 2017 |
| PCSeg: Color model driven probabilistic multiphase level set based tool for plasma cell segmentation in multiple myeloma A Gupta, P Mallick, O Sharma, R Gupta, R Duggal PloS one 13 (12), e0207908, 2018 | 31 | 2018 |
| Elf: An early-exiting framework for long-tailed classification R Duggal, S Freitas, S Dhamnani, DH Chau, J Sun arXiv preprint arXiv:2006.11979, 2020 | 29 | 2020 |
| P-TELU: Parametric tan hyperbolic linear unit activation for deep neural networks R Duggal, A Gupta Proceedings of the IEEE international conference on computer vision …, 2017 | 25 | 2017 |
| Compatibility-aware heterogeneous visual search R Duggal, H Zhou, S Yang, Y Xiong, W Xia, Z Tu, S Soatto Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 24 | 2021 |
| Rest: Robust and efficient neural networks for sleep monitoring in the wild R Duggal, S Freitas, C Xiao, DH Chau, J Sun Proceedings of The Web Conference 2020, 1704-1714, 2020 | 24 | 2020 |
| MalNet: A Large-Scale Image Database of Malicious Software S Freitas, R Duggal, DH Chau arXiv preprint arXiv:2102.01072, 2021 | 21 | 2021 |
| Cup: Cluster pruning for compressing deep neural networks R Duggal, C Xiao, R Vuduc, DH Chau, J Sun 2021 IEEE International Conference on Big Data (Big Data), 5102-5106, 2021 | 14 | 2021 |
| Neurocartography: Scalable automatic visual summarization of concepts in deep neural networks H Park, N Das, R Duggal, AP Wright, O Shaikh, F Hohman, DHP Chau IEEE Transactions on Visualization and Computer Graphics 28 (1), 813-823, 2021 | 14 | 2021 |
| SN-AM dataset: white blood cancer dataset of B-ALL and MM for stain normalization A Gupta, R Gupta Cancer Imaging Arch, 2019 | 12 | 2019 |
| Robotic instrument segmentation challenge. arXiv M Allan, A Shvets, T Kurmann, Z Zhang, R Duggal, YH Su, N Rieke, ... Preprint posted online February 21, 2019, 2017 | 11 | 2017 |
| Har: hardness aware reweighting for imbalanced datasets R Duggal, S Freitas, S Dhamnani, DH Chau, J Sun 2021 IEEE International Conference on Big Data (Big Data), 735-745, 2021 | 8 | 2021 |
| Robust principles: Architectural design principles for adversarially robust cnns SY Peng, W Xu, C Cornelius, M Hull, K Li, R Duggal, M Phute, J Martin, ... arXiv preprint arXiv:2308.16258, 2023 | 3 | 2023 |
| RobArch: Designing Robust Architectures against Adversarial Attacks SY Peng, W Xu, C Cornelius, K Li, R Duggal, DH Chau, J Martin arXiv preprint arXiv:2301.03110, 2023 | 2 | 2023 |
| Towards regression-free neural networks for diverse compute platforms R Duggal, H Zhou, S Yang, J Fang, Y Xiong, W Xia European Conference on Computer Vision, 598-614, 2022 | 2 | 2022 |
| ConceptEvo: Interpreting Concept Evolution in Deep Learning Training H Park, S Lee, B Hoover, A Wright, O Shaikh, R Duggal, N Das, J Hoffman, ... arXiv preprint arXiv:2203.16475, 2022 | 2 | 2022 |
Anubha GuptaIIIT-DelhiVerified email at iiitd.ac.in
