| Usability evaluation of learning management systems in Sri Lankan universities S Thuseethan, S Achchuthan, S Kuhanesan Global Journal of Computer Science and Technology 15 (1), 2015 | 69 | 2015 |
| Deep metric learning based citrus disease classification with sparse data S Janarthan, S Thuseethan, S Rajasegarar, Q Lyu, Y Zheng, J Yearwood IEEE Access 8, 162588-162600, 2020 | 60 | 2020 |
| Influence of Facebook in academic performance of Sri Lankan university students S Thuseethan, S Kuhanesan Global Journal of Computer Science and Technology, 14 (4), 2014 | 48 | 2014 |
| LGAttNet: Automatic micro-expression detection using dual-stream local and global attentions MA Takalkar, S Thuseethan, S Rajasegarar, Z Chaczko, M Xu, ... Knowledge-Based Systems 212, 106566, 2021 | 35 | 2021 |
| Deep continual learning for emerging emotion recognition S Thuseethan, S Rajasegarar, J Yearwood IEEE Transactions on Multimedia 24, 4367-4380, 2021 | 24 | 2021 |
| Social media as a new trend in Sri Lankan digital journalism: A surveillance T Selvarajah, V Shanmuganatha Deakin University, 2015 | 22 | 2015 |
| Effective use of human computer interaction in digital academic supportive devices S Thuseethan, S Kuhanesan arXiv preprint arXiv:1501.00529, 2015 | 20 | 2015 |
| Eigenface based recognition of emotion variant faces S Thuseethan, S Kuhanesan Computer Engineering and Intelligent Systems, 2016 | 19* | 2016 |
| Complex emotion profiling: An incremental active learning based approach with sparse annotations S Thuseethan, S Rajasegarar, J Yearwood IEEE Access 8, 147711-147727, 2020 | 16 | 2020 |
| Department Management System for Departments of Sri Lankan Universities S Thuseethan arXiv preprint arXiv:1501.00526, 2015 | 15 | 2015 |
| Emotion intensity estimation from video frames using deep hybrid convolutional neural networks S Thuseethan, S Rajasegarar, J Yearwood 2019 International Joint Conference on Neural Networks (IJCNN), 1-10, 2019 | 14 | 2019 |
| Deep3DCANN: A Deep 3DCNN-ANN framework for spontaneous micro-expression recognition S Thuseethan, S Rajasegarar, J Yearwood Information Sciences 630, 341-355, 2023 | 13 | 2023 |
| Detecting micro-expression intensity changes from videos based on hybrid deep CNN S Thuseethan, S Rajasegarar, J Yearwood Advances in Knowledge Discovery and Data Mining: 23rd Pacific-Asia …, 2019 | 13 | 2019 |
| Deep hybrid spatiotemporal networks for continuous pain intensity estimation S Thuseethan, S Rajasegarar, J Yearwood Neural Information Processing: 26th International Conference, ICONIP 2019 …, 2019 | 12 | 2019 |
| EmoSeC: Emotion recognition from scene context S Thuseethan, S Rajasegarar, J Yearwood Neurocomputing 492, 174-187, 2022 | 10 | 2022 |
| Positive and negative impacts of facebook on university students: Sri lankan perspective S Thuseethan, S Kuhanesan IUP Journal of Information Technology 10 (3), 7, 2014 | 10 | 2014 |
| P2OP—Plant Pathology on Palms: A deep learning-based mobile solution for in-field plant disease detection S Janarthan, S Thuseethan, S Rajasegarar, J Yearwood Computers and Electronics in Agriculture 202, 107371, 2022 | 9 | 2022 |
| Multimodal deep learning framework for sentiment analysis from text-image web Data S Thuseethan, S Janarthan, S Rajasegarar, P Kumari, J Yearwood 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and …, 2020 | 5 | 2020 |
| Boosting emotion recognition in context using non-target subject information S Thuseethan, S Rajasegarar, J Yearwood 2021 International Joint Conference on Neural Networks (IJCNN), 1-7, 2021 | 4 | 2021 |
| Prediction of human flow in disaster situations: A multi-agent based modelling and simulation S Vasanthapriyan, S Thuseethan 2015 2nd International Symposium on Dependable Computing and Internet of …, 2015 | 3 | 2015 |
John YearwoodDeakin UniversityVerified email at deakin.edu.au
