| 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 | 162 | 2019 |
| Random path selection for incremental learning J Rajasegaran, M Hayat, S Khan, FS Khan, L Shao Advances in Neural Information Processing Systems, 2019 | 93* | 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 | 57 | 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 | 49 | 2019 |
| 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 | 29 | 2018 |
| Self-supervised knowledge distillation for few-shot learning J Rajasegaran, S Khan, M Hayat, FS Khan, M Shah arXiv preprint arXiv:2006.09785, 2020 | 27 | 2020 |
| Incremental Object Detection via Meta-Learning J Kj, J Rajasegaran, S Khan, FS Khan, VN Balasubramanian IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 14* | 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 | 13* | 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 | 8 | 2017 |
| TimeCaps: Capturing Time Series Data with Capsule Networks H Jayasekara, V Jayasundara, J Rajasegaran, S Jayasekara, ... ArXiv, abs/1911.11800, 2019 | 5* | 2019 |
| Tracking People with 3D Representations J Rajasegaran, G Pavlakos, A Kanazawa, J Malik arXiv preprint arXiv:2111.07868, 2021 | 3 | 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 | 2 | 2020 |
| 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 |
| 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 | | 2022 |
| Meta-learning the Learning Trends Shared Across Tasks J Rajasegaran, S Khan, M Hayat, FS Khan, M Shah arXiv preprint arXiv:2010.09291, 2020 | | 2020 |
Suranga SeneviratneUniversity of SydneyAdresse e-mail validée de sydney.edu.au
