Research on Sports Training Action Recognition Based on Deep Learning | Zendy

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Research on Sports Training Action Recognition Based on Deep Learning

Author(s) -

Wang Peng

Publication year - 2021

Publication title -

scientific programming

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.269

H-Index - 36

eISSN - 1875-919X

pISSN - 1058-9244

DOI - 10.1155/2021/3396878

Subject(s) - computer science , action recognition , artificial intelligence , digitization , field (mathematics) , motion (physics) , action (physics) , deep learning , human–computer interaction , computer vision , physics , mathematics , quantum mechanics , pure mathematics , class (philosophy)

With the rapid development of science and technology in today’s society, various industries are pursuing information digitization and intelligence, and pattern recognition and computer vision are also constantly carrying out technological innovation. Computer vision is to let computers, cameras, and other machines receive information like human beings, analyze and process their semantic information, and make coping strategies. As an important research direction in the field of computer vision, human motion recognition has new solutions with the gradual rise of deep learning. Human motion recognition technology has a high market value, and it has broad application prospects in the fields of intelligent monitoring, motion analysis, human-computer interaction, and medical monitoring. This paper mainly studies the recognition of sports training action based on deep learning algorithm. Experimental work has been carried out in order to show the validity of the proposed research.

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