LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Wushu Routine Movement and Diagnosis Based on Deep Learning and Symmetric Difference Algorithm

Photo from wikipedia

Wushu is one of the traditional cultural symbols of the Chinese nation. It is also one of the most popular sports activities among the people. With the attention and love… Click to show full abstract

Wushu is one of the traditional cultural symbols of the Chinese nation. It is also one of the most popular sports activities among the people. With the attention and love of contemporary people to sports activities, Wushu is also constantly developing and innovating. The requirements for professional martial arts routines of martial arts athletes are higher than ever. The development of martial arts has also made martial arts competitions more intense, and often a small detail of martial arts movements can determine the success or failure of the competition. Therefore, various Wushu teams pay more and more attention to the analysis and diagnosis of Wushu routines. It ensures that coaches and athletes can obtain more quantitative indicators of technical movement training. The analysis and diagnosis of martial arts routines are inseparable from the support of reliable science and technology and related algorithms. This article aims to study the analysis and diagnosis of martial arts routines based on deep learning and symmetric difference algorithm. It combines deep learning and symmetric difference algorithm to analyze and diagnose martial arts routines. The article concludes that the level of martial arts routines of martial arts athletes has the greatest influence on their martial arts competition performance, and its comprehensive influence index is as high as 4.3.

Keywords: martial arts; diagnosis; symmetric difference; learning symmetric; arts routines; deep learning

Journal Title: Computational Intelligence and Neuroscience
Year Published: 2022

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.