A Football Shot Action Recognition Method Based on Deep Learning Algorithm

Author:

Xue Ming1,Chen Hongtao2ORCID

Affiliation:

1. College of Physical Education, Hunan International Economics University, Changsha 410205, Hunan, China

2. School of Physical Education and Health, Yulin Normal University, Yulin 537000, Guangxi, China

Abstract

Football is regarded as the world’s number one sport and is loved by all countries, and large-scale football matches are held basically every year. The key to football matches is to shoot goals, and how to improve the accuracy of football shooting requires the identification and analysis of football shooting actions. Deep learning enables machines to imitate human activities such as seeing, hearing, and thinking. It solves many complex pattern recognition problems. Especially, the deep learning algorithm is unique in the recognition of pictures with high accuracy, and it provides technical support for the recognition and analysis of football shooting actions. What this paper will discuss is the recognition method of football shooting action based on a deep learning algorithm. Experiments show that the football shooting action recognition method developed in this paper has a great effect on promoting the accuracy of football shooting, which can make the accuracy rate reach about 96%. The research in this paper has great reference value and practical significance for the team’s ability to shoot and grasp the opportunity to score.

Publisher

Hindawi Limited

Subject

Computer Science Applications,Software

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Artificial intelligence applications in the football codes: A systematic review;Journal of Sports Sciences;2024-07-02

2. Performance Analysis for Diving Sport Using YoLoV8, OpenPose and Fuzzy Logic;2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE);2024-02-22

3. Recognition of Recurrent Movement Patterns of Football Players via Machine Learning;2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE);2022-10-26

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