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Updated: Jan 9, 2026

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轻量级的注意力增强YOLOv5s用于在老年护理环境中准确和实时的摔倒检测

Bibo Yang1, Lan Thi Nguyen1, Wirapong Chansanam1

  • 1Department of Information Science, Faculty of Humanities and Social Sciences, Khon Kaen University, Khon Kaen 40002, Thailand.

Sensors (Basel, Switzerland)
|December 11, 2025
PubMed
概括

这项研究引入了一种改进的YOLOv5s模型,用于准确的,实时的老年人落检测. 人工智能框架通过优化特征提取和融合来增强老龄化社会的安全监测.

关键词:
卷积式区块注意模块 (CBAM) 的使用这是YOLOv5s.老年人护理监测监控老年人的护理落检测系统 落检测系统 落检测系统多级特征聚变的多级特征聚变

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