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Updated: May 9, 2025

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意识到不确定性的拓性持久性引导知识蒸在可穿戴传感器数据上的数据

Eun Som Jeon1, Matthew P Buman2, Pavan Turaga1

  • 1Geometric Media Lab, School of Arts, Media and Engineering and School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85281 USA.

IEEE internet of things journal
|May 1, 2025
PubMed
概括

拓数据分析 (TDA) 功能改进了可穿戴传感器分析,但计算密集. 我们的知识蒸方法使用不确定性意识的拓持久性创建了一个紧的模型,提高了4.3%的性能.

关键词:
知识的蒸知识的蒸.时间序列数据分析数据分析.拓学数据分析数据分析.可穿戴式传感器数据数据

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