Graph Convolutional Networks Skeleton-based Action Recognition for Continuous Data Stream: A Sliding Window Approach
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Affiliation:
1. SIAtech SAS, 73 Rue Martainville, 76000 Rouen, France, --- Select a Country ---
2. Normandie Univ., UNIROUEN, ESIGELEC, IRSEEM, 76000 Rouen, France, --- Select a Country ---
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SCITEPRESS - Science and Technology Publications
Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Enhanced Spatio- Temporal Image Encoding for Online Human Activity Recognition;2023 International Conference on Machine Learning and Applications (ICMLA);2023-12-15
2. Deep learning for graph analysis: application to online human activity recognition;2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom);2023-11-01
3. Accurate continuous action and gesture recognition method based on skeleton and sliding windows techniques;2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC);2023-10-31
4. Towards Recognition of Human Actions in Collaborative Tasks with Robots: Extending Action Recognition with Tool Recognition Methods;Sensors;2023-06-19
5. Action Classification in Human Robot Interaction Cells in Manufacturing;Proceedings of the 2023 8th International Conference on Machine Learning Technologies;2023-03-10
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