Design of tennis auxiliary teaching system based on reinforcement learning and multi-feature fusion

To accurately identify and evaluate tennis movements, a tennis auxiliary teaching system based on reinforcement learning and multi-feature fusion was designed by combining deep learning methods with tennis-related knowledge to recognize and evaluate tennis movements accurately. The algorithm first e...

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Veröffentlicht in:	PeerJ. Computer science Jg. 11; S. e3188
Hauptverfasser:	Zhang, Shiquan, Gan, Chaohong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States PeerJ. Ltd 09.09.2025 PeerJ Inc
Schlagworte:	Algorithms Artificial neural networks Education Human pose recognition algorithm Machine learning Methods Multi feature fusion Reinforcement learning Tennis Multi feature fusion Human pose recognition algorithm Artificial neural networks Reinforcement learning
ISSN:	2376-5992, 2376-5992
Online-Zugang:	Volltext
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