Tennis teaching assistance model based on double chain shared unsupervised action recognition algorithm

The traditional self-supervised methods based on skeleton data frequently categorize the various enhancements of a given sample as positive examples, while the remaining samples are designated as negative examples. This approach results in a significant imbalance in the ratio of positive to negative...

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Bibliographic Details

Published in:	International Journal of Cognitive Computing in Engineering
Main Author:	Hongzhou Bai
Format:	Article
Language:	English
Published:	KeAi Communications Co., Ltd. 2025-12-01
Subjects:	Action recognition Unsupervised learning Data augmentation Human skeleton Positive sample expansion
Online Access:	http://www.sciencedirect.com/science/article/pii/S2666307424000433