| DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG A Supratak, H Dong, C Wu, Y Guo IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2017 | 1093 | 2017 |
| Mixed neural network approach for temporal sleep stage classification H Dong, A Supratak, W Pan, C Wu, PM Matthews, Y Guo IEEE Transactions on Neural Systems and Rehabilitation Engineering 26 (2 …, 2018 | 288 | 2018 |
| TinySleepNet: An efficient deep learning model for sleep stage scoring based on raw single-channel EEG A Supratak, Y Guo 2020 42nd Annual International Conference of the IEEE Engineering in …, 2020 | 175 | 2020 |
| Tensorlayer: a versatile library for efficient deep learning development H Dong, A Supratak, L Mai, F Liu, A Oehmichen, S Yu, Y Guo Proceedings of the 25th ACM international conference on Multimedia, 1201-1204, 2017 | 124 | 2017 |
| Using support vector machine on EEG for advertisement impact assessment Z Wei, C Wu, X Wang, A Supratak, P Wang, Y Guo Frontiers in neuroscience 12, 76, 2018 | 85 | 2018 |
| Feature extraction with stacked autoencoders for epileptic seizure detection A Supratak, L Li, Y Guo 2014 36th Annual international conference of the IEEE engineering in …, 2014 | 77 | 2014 |
| Survey on feature extraction and applications of biosignals A Supratak, C Wu, H Dong, K Sun, Y Guo Machine Learning for Health Informatics: State-of-the-Art and Future …, 2016 | 43 | 2016 |
| Remote Monitoring in the Home Validates Clinical Gait Measures for Multiple Sclerosis A Supratak, G Datta, AR Gafson, R Nicholas, Y Guo, PM Matthews Frontiers in Neurology 9, 561, 2018 | 33 | 2018 |
| A lightweight deep learning approach to mosquito classification from wingbeat sounds MS Yin, P Haddawy, B Nirandmongkol, T Kongthaworn, ... Proceedings of the conference on information technology for social good, 37-42, 2021 | 22 | 2021 |
| A deep learning-based pipeline for mosquito detection and classification from wingbeat sounds MS Yin, P Haddawy, T Ziemer, F Wetjen, A Supratak, K Chiamsakul, ... Multimedia Tools and Applications 82 (4), 5189-5205, 2023 | 18 | 2023 |
| Machine learning for health informatics A Supratak, C Wu, H Dong, K Sun, Y Guo Springer, 2016 | 14 | 2016 |
| Enabling performance as a service for a cloud storage system Y Li, L Guo, A Supratak, Y Guo 2014 IEEE 7th International Conference on Cloud Computing, 554-561, 2014 | 8 | 2014 |
| Objective scoring of footpad dermatitis in broiler chickens using image segmentation and a deep learning approach: camera-based scoring system C Kaewtapee, S Thepparak, C Rakangthong, C Bunchasak, A Supratak British Poultry Science 63 (4), 427-433, 2022 | 5 | 2022 |
| A study of expert/novice perception in arthroscopic shoulder surgery MS Yin, P Haddawy, B Hosp, P Sa-Ngasoongsong, T Tanprathumwong, ... Proceedings of the 4th International Conference on Medical and Health …, 2020 | 5 | 2020 |
| Automatic measurement of acidity from roasted coffee beans images using efficient deep learning P Sajjacholapunt, A Supratak, S Tuarob Journal of Food Process Engineering, e14147, 2022 | 4 | 2022 |
| Yolk color measurement using image processing and deep learning C Kaewtapee, A Supratak IOP Conference Series: Earth and Environmental Science 686 (1), 012054, 2021 | 4 | 2021 |
| Quantifying the impact of data characteristics on the transferability of sleep stage scoring models A Supratak, P Haddawy Artificial Intelligence in Medicine 139, 102540, 2023 | 3 | 2023 |
| Remote Actigraphy for Quantitative Assessment of Walking Speed in People with MS A Supratak, G Datta, C Wu, S Yu, C D'Arcy, R Nicholas, Y Guo, ... Neurology 86 (16 Supplement), P3. 309, 2016 | 3 | 2016 |
| Towards Desynchronization Detection in Biosignals A Supratak, S Schneider, H Dong, L Li, Y Guo NIPS Time Series Workshop, 2017 | 2 | 2017 |
| The Diagnostic Accuracy of Artificial Intelligence in Radiological Markers of Normal-Pressure Hydrocephalus (NPH) on Non-Contrast CT Scans of the Brain D Songsaeng, P Nava-Apisak, J Wongsripuemtet, S Kingchan, ... Diagnostics 13 (17), 2840, 2023 | 1 | 2023 |
