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Updated: May 10, 2026

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
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Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

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为残疾人使用人工智能与蛇形优化技术的先进智能人类活动识别系统

Manal Abdullah Alohali1, Mohammed Yahya Alzahrani2, Asmaa Mansour Alghamdi3

  • 1Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia. maalohaly@pnu.edu.sa.

Scientific reports
|August 26, 2025
PubMed
概括

这项研究介绍了使用深度学习与蛇优化器 (AHARDP-DLSO) 方法对残疾人进行高级智能人类活动识别. AHARDP-DLSO模型在识别残疾人的日常活动方面达到95.81%的准确性.

关键词:
深层信念网络深度学习残疾人人类活动的认可蛇优化算法

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