| A taxonomy of deep convolutional neural nets for computer vision S Srinivas, RK Sarvadevabhatla, KR Mopuri, N Prabhu, SSS Kruthiventi, ... Frontiers in Robotics and AI 2, 36, 2016 | 217 | 2016 |
| Fast feature fool: A data independent approach to universal adversarial perturbations KR Mopuri, U Garg, RV Babu Proccedings of British Machine Vision Conference (BMVC), 2017 | 181 | 2017 |
| idlg: Improved deep leakage from gradients B Zhao, KR Mopuri, H Bilen arXiv preprint arXiv:2001.02610, 2020 | 154 | 2020 |
| Generalizable data-free objective for crafting universal adversarial perturbations KR Mopuri, A Ganeshan, VB Radhakrishnan IEEE transactions on pattern analysis and machine intelligence, 2018 | 146 | 2018 |
| Zero-shot knowledge distillation in deep networks GK Nayak, KR Mopuri, V Shaj, VB Radhakrishnan, A Chakraborty International Conference on Machine Learning, 4743-4751, 2019 | 143 | 2019 |
| NAG: Network for Adversary Generation KR Mopuri, U Ojha, U Garg, RV Babu The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018 | 115 | 2018 |
| Object level deep feature pooling for compact image representation K Reddy Mopuri, R Venkatesh Babu Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 69 | 2015 |
| Ask, acquire, and attack: Data-free uap generation using class impressions KR Mopuri, PK Uppala, RV Babu Proceedings of the European Conference on Computer Vision (ECCV), 19-34, 2018 | 63 | 2018 |
| Cnn fixations: an unraveling approach to visualize the discriminative image regions KR Mopuri, U Garg, RV Babu IEEE Transactions on Image Processing 28 (5), 2116-2125, 2018 | 46 | 2018 |
| Dataset Condensation with Gradient Matching. B Zhao, KR Mopuri, H Bilen ICLR 1 (2), 3, 2021 | 32 | 2021 |
| An introduction to deep convolutional neural nets for computer vision S Srinivas, RK Sarvadevabhatla, KR Mopuri, N Prabhu, SSS Kruthiventi, ... Deep Learning for Medical Image Analysis, 25-52, 2017 | 29 | 2017 |
| Dataset condensation with gradient matching B Zhao, KR Mopuri, H Bilen arXiv preprint arXiv:2006.05929, 2020 | 24 | 2020 |
| Gray-box adversarial training BS Vivek, KR Mopuri, RV Babu Proceedings of the European conference on computer vision (ECCV), 203-218, 2018 | 23 | 2018 |
| Early stuck pipe sign detection with depth-domain 3D convolutional neural network using actual drilling data N Tsuchihashi, R Wada, M Ozaki, T Inoue, KR Mopuri, H Bilen, ... SPE Journal 26 (02), 551-562, 2021 | 12 | 2021 |
| Bilen, H. idlg: Improved deep leakage from gradients B Zhao, KR Mopuri arXiv preprint arXiv:2001.02610, 2020 | 11 | 2020 |
| Effectiveness of arbitrary transfer sets for data-free knowledge distillation GK Nayak, KR Mopuri, A Chakraborty Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 9 | 2021 |
| Spatio-temporal feature based VLAD for efficient video retrieval MK Reddy, S Arora, RV Babu 2013 Fourth National Conference on Computer Vision, Pattern Recognition …, 2013 | 8 | 2013 |
| Sparse coding based VLAD for efficient image retrieval MK Reddy, J Talur, RV Babu 2014 IEEE International Conference on Electronics, Computing and …, 2014 | 7 | 2014 |
| Gray-box Adversarial Training KR Mopuri, RV Babu arXiv preprint arXiv:1808.01753, 2018 | 4 | 2018 |
| Gray-box Adversarial Training KR Mopuri, RV Babu arXiv preprint arXiv:1808.01753, 2018 | 4 | 2018 |
R. Venkatesh BabuCDS, Indian Institute of Science, Bangalore, IndiaPotvrđena adresa e-pošte na iisc.ac.in
