| SoccerCPD: Formation and Role Change-Point Detection in Soccer Matches using Spatiotemporal Tracking Data H Kim, B Kim, D Chung, J Yoon, SK Ko ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 3146-3156, 2022 | 14 | 2022 |
| A Deep Learning Approach for Fatigue Prediction in Sports using GPS Data and Rate of Perceived Exertion J Kim, H Kim, J Lee, J Lee, J Yoon, SK Ko IEEE Access 10, 103056-103064, 2022 | 11 | 2022 |
| Ball Trajectory Inference from Multi-Agent Sports Contexts using Set Transformer and Hierarchical Bi-LSTM H Kim, HJ Choi, C Kim, J Yoon, SK Ko ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 4296-4307, 2023 | 8 | 2023 |
| 6MapNet: Representing Soccer Players from Tracking Data by a Triplet Network H Kim, J Kim, D Chung, J Lee, J Yoon, SK Ko ECML PKDD Workshop on Machine Learning for Sports Analytics (MLSA), 2021 | 7 | 2021 |
| Pass Receiver and Outcome Prediction in Soccer using Temporal Graph Networks P Rahimian, H Kim, M Schmid, L Toka ECML PKDD Workshop on Machine Learning for Sports Analytics (MLSA), 2023 | 4 | 2023 |
| DBHP: Trajectory Imputation in Multi-Agent Sports using Derivative-Based Hybrid Prediction H Choi*, H Kim*, M Lee, C Kim, J Yoon, SK Ko arXiv preprint arXiv:2408.10878, 2024 | | 2024 |
| Contextual Sprint Classification in Soccer Based on Deep Learning H Kim, GH Joe, J Yoon, SK Ko IJCAI Workshop on Intelligent Technologies for Precision Sports Science (IT4PSS), 2024 | | 2024 |
| Cost-Efficient and Bias-Robust Sports Player Tracking by Integrating GPS and Video H Kim, C Kim, M Jeong, J Lee, J Yoon, SK Ko ECML PKDD Workshop on Machine Learning for Sports Analytics (MLSA), 2022 | | 2022 |
Sang-Ki KoUniversity of Seoul在 uos.ac.kr 的电子邮件经过验证
