基于改进深度学习算法的大学生行为识别

Q2 Social Sciences
Xiao Ning
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引用次数: 0

摘要

随着智能化校园建设的蓬勃发展,高校信息技术的发展也发生了巨大的变化,由以往的数字化向智能化发展。在教学过程中,对学生课堂学习的分析也从以往的人工观察转变为智能分析。基于此,本文研究了基于改进深度学习算法的大学生行为识别。在简要分析行为识别研究背景的基础上,构建了大学生行为识别的研究框架。最后,笔者设计了一个实验来评估课堂学生行为识别分析的准确性。结果表明,基于深度学习算法改进的大学生行为识别可以提高识别精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Behavior Recognition of College Students Based on Improved Deep Learning Algorithm
With the vigorous development of intelligent campus construction, great changes have taken place in the development of information technology in colleges and universities from the previous digital to intelligent development. In the teaching process, the analysis of students' classroom learning has also changed from the previous manual observation to intelligent analysis. Based on this, this paper studies the behavior recognition of college students based on the improved deep learning algorithm. Based on a brief analysis of the research background of behavior recognition, the research framework of college students' behavior recognition is constructed. Finally, the authors designed an experiment to evaluate the accuracy of classroom student behavior recognition analysis. The results show that the improved recognition of college students' behavior based on deep learning algorithm can improve the recognition accuracy.
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CiteScore
2.40
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0.00%
发文量
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