Cost-Efficient and Bias-Robust Sports Player Tracking by Integrating GPS and Video
Gespeichert in:
| Veröffentlicht in: | International Workshop on Machine Learning and Data Mining for Sports Analytics (9. : 2022 : Grenoble) Machine learning and data mining for sports analytics |
|---|---|
| 1. Verfasser: | |
| Weitere Verfasser: | , , , , |
| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
2023
|
| Schlagworte: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Tag hinzufügen | Titel | Jahr | Verfasser |
|---|---|---|
| Shot Analysis in Different Levels of German Football Using Expected Goals | 2023 | Raudonius, Laurynas |
| Discovering and Visualizing Tactics in a Table Tennis Game Based on Subgroup Discovery | 2023 | Duluard, Pierre |
| Towards Expected Counter - Using Comprehensible Features to Predict CoUunterattacks | 2023 | Biermann, Henrik |
| Evaluation of Creating Scoring Opportunities for Teammates in Soccer via Trajectory Prediction | 2023 | Teranishi, Masakiyo |
| Let’s Penetrate the Defense: A Machine Learning Model for and Prediction Valuation of Penetrative Passes | 2023 | Rahimian, Pegah |
| Cost-Efficient and Bias-Robust Sports Player Tracking by Integrating GPS and Video | 2023 | Kim, Hyunsung |
| Predicting Tennis Serve Directions with Machine Learning | 2023 | Zhu, Ying |
| Athlete Monitoring in Professional Road Cycling Using Similarity Search on Time Series Data | 2023 | Leeuw, Arie-Willem de |
| Analyzing Passing Sequences for the Prediction of Goal-Scoring Opportunities | 2023 | McCarthy, Conor |