| Deepcaps: Going deeper with capsule networks J Rajasegaran, V Jayasundara, S Jayasekara, H Jayasekara, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 202 | 2019 |
| Random path selection for continual learning J Rajasegaran, M Hayat, SH Khan, FS Khan, L Shao Advances in Neural Information Processing Systems 32, 2019 | 138* | 2019 |
| itaml: An incremental task-agnostic meta-learning approach J Rajasegaran, S Khan, M Hayat, FS Khan, M Shah Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 104 | 2020 |
| Textcaps: Handwritten character recognition with very small datasets V Jayasundara, S Jayasekara, H Jayasekara, J Rajasegaran, ... 2019 IEEE winter conference on applications of computer vision (WACV), 254-262, 2019 | 62 | 2019 |
| Self-supervised knowledge distillation for few-shot learning J Rajasegaran, S Khan, M Hayat, FS Khan, M Shah arXiv preprint arXiv:2006.09785, 2020 | 55 | 2020 |
| Performance characterization of deep learning models for breathing-based authentication on resource-constrained devices J Chauhan, J Rajasegaran, S Seneviratne, A Misra, A Seneviratne, Y Lee Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2018 | 39 | 2018 |
| Incremental object detection via meta-learning KJ Joseph, J Rajasegaran, S Khan, FS Khan, VN Balasubramanian IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (12), 9209 …, 2021 | 32 | 2021 |
| A multi-modal neural embeddings approach for detecting mobile counterfeit apps: A case study on Google Play store N Karunanayake, J Rajasegaran, A Gunathillake, S Seneviratne, ... IEEE Transactions on Mobile Computing 21 (1), 16-30, 2020 | 17* | 2020 |
| Tracking people with 3D representations J Rajasegaran, G Pavlakos, A Kanazawa, J Malik arXiv preprint arXiv:2111.07868, 2021 | 12 | 2021 |
| Power control for body area networks: Accurate channel prediction by lightweight deep learning Y Yang, D Smith, J Rajasegaran, S Seneviratne IEEE Internet of Things Journal 8 (5), 3567-3575, 2020 | 9 | 2020 |
| Combined static and motion features for deep-networks-based activity recognition in videos S Ramasinghe, J Rajasegaran, V Jayasundara, K Ranasinghe, ... IEEE Transactions on Circuits and Systems for Video Technology 29 (9), 2693-2707, 2017 | 9 | 2017 |
| Meta-learning the learning trends shared across tasks J Rajasegaran, S Khan, M Hayat, FS Khan, M Shah arXiv preprint arXiv:2010.09291, 2020 | 7 | 2020 |
| DeepCaps: Going Deeper With Capsule Networks. 2019 IEEE J Rajasegaran, V Jayasundara, S Jayasekara, H Jayasekara, ... CVF Conference on Computer Vision and Pattern Recognition (CVPR), 10717-10725, 2019 | 7 | 2019 |
| Tracking People by Predicting 3D Appearance, Location & Pose J Rajasegaran, G Pavlakos, A Kanazawa, J Malik Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 5 | 2022 |
| Timecaps: Capturing time series data with capsule networks H Jayasekara, V Jayasundara, J Rajasegaran, S Jayasekara, ... ArXiv, 2019 | 5* | 2019 |
| Micro Actions and Deep Static Features for Activity Recognition S Ramasinghe, J Rajasegaran, V Jayasundara, K Ranasinghe, ... 2017 International Conference on Digital Image Computing: Techniques and …, 2017 | 1 | 2017 |
| Fully Online Meta-Learning Without Task Boundaries J Rajasegaran, C Finn, S Levine arXiv preprint arXiv:2202.00263, 2022 | | 2022 |
| Mitigating Mode Collapse by Sidestepping Catastrophic Forgetting K Mangalam, R Garg, J Rajasegaran, T Park | | |
Suranga SeneviratneUniversity of SydneyVerified email at sydney.edu.au
