Research on the application technology of Artificial Intelligence in college physical education and training

Author:

Mao Min1,Chen Jianxing1

Affiliation:

1. Jiujiang Univ , Dept Physical Education , JiuJiang , Jiangxi Province , China , 332005.

Abstract

Abstract Nowadays, with the swift advancement of Artificial Intelligence (AI) technology, its applications have become widespread across diverse fields. AI is no longer a mere abstract idea but has seamlessly integrated into our daily lives, bringing numerous conveniences through its myriad benefits. One such domain where AI has made significant inroads in college physical education and training. The integration of Intelligent Computer-Aided Instruction (ICAI) with computer-assisted teaching systems, AI-powered wearable devices, motion capture systems in sports training, and virtual demonstration technology for simulating athletic movements has greatly enhanced both the precision of physical education and the efficacy of physical training. AI continues to evolve rapidly, indicating vast potential for further development in its integration with physical education and training. This paper highlights the widespread adoption of AI in sports and delves into its specific applications within this domain. The findings reveal that the algorithm employed in this context excels in identifying sports movement features, outperforming the comparison algorithm by 27.65%. Moreover, it precisely pinpoints the edge contours of human movement. In comparison to traditional Support Vector Machines (SVM), Convolutional Neural Networks (CNN) exhibit clear advantages during the later stages of operation, reducing errors by 36.69%. The experimental results underscore the importance of comprehensive human body detection in ensuring stable and accurate sports action tracking.

Publisher

Walter de Gruyter GmbH

Reference26 articles.

1. Automation and Instrumentation. (2016). Application of three-dimensional motion capture system in physical education teaching, (12), 43-44.

2. Zhang, W. (2018). Application of Intelligent Internet Technology in Physical Education. China School Physical Education, 5, 35-36.

3. Yuan, S. (2018). The development trend of physical training and the transformation of digital intelligence. Sports Research, 1(002), 77-85.

4. Li, J. (2020). Analysis and Prospect of Sports Coaching System Based on Artificial Intelligence. Electronics World, 589(07), 45-46.

5. Escalante-B., A. N., & Wiskott, L. (2016). Theoretical Analysis of the Optimal Free Responses of Graph-Based SFA for the Design of Training Graphs. Journal of Machine Learning Research, 17(157), 1-36.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3