利用人工封闭样本来增强人类活动识别中的数据

Eirini Mathe1, Ioannis Vernikos2, Evaggelos Spyrou2

  • 1Department of Informatics and Computer Engineering, University of West Attica, 12243 Athens, Greece.

PubMed
概括

这项研究引入了一种新的数据增强技术,用于通过模拟骨架数据中的阻塞来进行人类活动识别 (HAR). 这种方法提高了模型的稳定性和性能,解决了当前深度学习方法的局限性.

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