| Intelligent IoT connectivity: Deep reinforcement learning approach M Kwon, J Lee, H Park IEEE Sensors Journal 20 (5), 2782-2791, 2019 | 55 | 2019 |
| Analysis of gait sub-movements to estimate ataxia severity using ankle inertial data J Lee, B Oubre, JF Daneault, CD Stephen, JD Schmahmann, AS Gupta, ... IEEE Transactions on Biomedical Engineering 69 (7), 2314-2323, 2022 | 14 | 2022 |
| Multiple kernel learning with hierarchical feature representations J Lee, JH Lim, H Choi, DS Kim Neural Information Processing: 20th International Conference, ICONIP 2013 …, 2013 | 5 | 2013 |
| Envisioning the use of in-situ arm movement data in stroke rehabilitation: Stroke survivors’ and occupational therapists’ perspectives HT Jung, Y Kim, J Lee, SI Lee, EK Choe Plos one 17 (10), e0274142, 2022 | 2 | 2022 |
| Estimating the quality of reaching movements in stroke survivors J Lee, HT Jung, SI Lee 2021 IEEE EMBS International Conference on Biomedical and Health Informatics …, 2021 | 1 | 2021 |
| Learning to Activate Relay Nodes: Deep Reinforcement Learning Approach M Kwon, J Lee, H Park arXiv preprint arXiv:1811.09759, 2018 | 1 | 2018 |
| Estimation of ataxia severity in children with ataxia-telangiectasia using ankle-worn sensors J Lee, B Oubre, JF Daneault, SI Lee, AS Gupta Journal of Neurology 270 (10), 5097-5101, 2023 | | 2023 |
| Apparent volitional behavior selection based on memory predictions JC Park, JH Yoo, J Lee, DS Kim Neural Information Processing: 19th International Conference, ICONIP 2012 …, 2012 | | 2012 |
