| Deep Learning for Medical Anomaly Detection--A Survey T Fernando, H Gammulle, S Denman, S Sridharan, C Fookes ACM Computing Surveys (CSUR), 2021 | 288 | 2021 |
| Two stream lstm: A deep fusion framework for human action recognition H Gammulle, S Denman, S Sridharan, C Fookes 2017 IEEE winter conference on applications of computer vision (WACV), 177-186, 2017 | 221 | 2017 |
| Predicting the future: A jointly learnt model for action anticipation H Gammulle, S Denman, S Sridharan, C Fookes Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 114 | 2019 |
| Fine-grained action segmentation using the semi-supervised action GAN H Gammulle, S Denman, S Sridharan, C Fookes Pattern Recognition 98, 107039, 2020 | 46 | 2020 |
| TMMF: Temporal multi-modal fusion for single-stage continuous gesture recognition H Gammulle, S Denman, S Sridharan, C Fookes IEEE Transactions on Image Processing 30, 7689-7701, 2021 | 41 | 2021 |
| Forecasting future action sequences with neural memory networks H Gammulle, S Denman, S Sridharan, C Fookes The British Machine Vision Conference (BMVC) 2019, 2019 | 39 | 2019 |
| Multi-level sequence GAN for group activity recognition H Gammulle, S Denman, S Sridharan, C Fookes Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth …, 2019 | 32 | 2019 |
| Coupled generative adversarial network for continuous fine-grained action segmentation H Gammulle, T Fernando, S Denman, S Sridharan, C Fookes 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 200-209, 2019 | 27 | 2019 |
| Vision-based activity recognition in children with autism-related behaviors P Wei, D Ahmedt-Aristizabal, H Gammulle, S Denman, MA Armin Heliyon 9 (6), 2023 | 26 | 2023 |
| Continuous Human Action Recognition for Human-Machine Interaction: A Review H Gammulle, D Ahmedt-Aristizabal, S Denman, L Tychsen-Smith, ... ACM Computing Surveys (CSUR), 2023 | 24 | 2023 |
| Deep Learning for Medical Anomaly Detection-A Survey. T Fernando, H Gammulle, S Denman, S Sridharan, C Fookes ACM Comput. Surv. 54 (7), 141:1-141:37, 2022 | 23 | 2022 |
| Two-stream deep feature modelling for automated video endoscopy data analysis H Gammulle, S Denman, S Sridharan, C Fookes Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 17 | 2020 |
| Fuzzy logic based mobile robot target tracking in dynamic hostile environment T Fernando, H Gammulle, C Walgampaya 2015 IEEE International Conference on Computational Intelligence and Virtual …, 2015 | 13* | 2015 |
| Towards On-Board Panoptic Segmentation of Multispectral Satellite Images T Fernando, C Fookes, H Gammulle, S Denman, S Sridharan IEEE Transactions on Geoscience and Remote Sensing, 2023 | 8 | 2023 |
| Hierarchical Attention Network for Action Segmentation H Gammulle, S Denman, S Sridharan, C Fookes Pattern Recognition Letters 131, 442-448, 2020 | 6 | 2020 |
| Multi-Slice Net: A novel light weight framework for COVID-19 Diagnosis H Gammulle, T Fernando, S Sridharan, S Denman, C Fookes IEEE International Conference on Autonomous Systems 2021, 2021 | 4 | 2021 |
| Remembering What Is Important: A Factorised Multi-Head Retrieval and Auxiliary Memory Stabilisation Scheme for Human Motion Prediction T Fernando, H Gammulle, S Sridharan, S Denman, C Fookes IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 1 | 2024 |
| Physics Augmented Tuple Transformer for Autism Severity Level Detection C Ranasingha, H Gammulle, T Fernando, S Sridharan, C Fookes IEEE Sensors Journal, 2024 | | 2024 |
| Learning Through Guidance: Knowledge Distillation for Endoscopic Image Classification H Gammulle, Y Chen, S Sridharan, T Klein, C Fookes arXiv preprint arXiv:2308.08731, 2023 | | 2023 |
| Deep learning for human action understanding PH Gammulle Queensland University of Technology (QUT), 2019 | | 2019 |
Clinton FookesQueensland University of TechnologyVerified email at qut.edu.au
