PE Classroom Teaching Innovation Based on Deep Learning from the Perspective of New Curriculum Standard
In recent years, due to the influence of various factors, most of the physical quality of primary and secondary school students in China are in a state of subhealth. According to relevant studies, nearly 70 percent of Chinese students lack daily physical exercise. Physical quality is the primary factor and prerequisite of study and work, so how to improve the physical quality of primary and middle school students has become the top priority of physical education. Based on the requirements and guidance of China's physical education in the new curriculum standard, this paper innovates China's physical education classroom teaching to a certain extent based on deep learning algorithm. The final results show that the students who choose PE class based on deep learning algorithm account for about 85% of the total number of students, which exceeds the students who choose traditional PE class by 70%. Therefore, we believe that the estimation and recognition of students' movement posture in PE class can not only greatly improve students' enthusiasm for physical exercise but also avoid sports injuries caused by inaccurate operation in the process of exercise. Human posture estimation is to detect the position of each part of the human body from the image and calculate its direction and scale information. The advent of the era of big data is based on the relationship between multiple frames of images, while human posture recognition is based on the processing of single-frame static images. Correctly recognizing the pose information of multiple frames of continuous images still makes it possible to realize correct behavior analysis and understanding.
|WOS Research Area|
Computer Science ; Engineering ; Telecommunications
Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
|WOS Accession No|
|EI Accession Number|
Curricula ; Deep learning ; Learning algorithms ; Sports ; Sports medicine
|ESI Classification Code|
Ergonomics and Human Factors Engineering:461.4 ; Medicine and Pharmacology:461.6 ; Machine Learning:723.4.2 ; Education:901.2
|ESI Research Field|
Cited Times [WOS]:0
|Document Type||Journal Article|
|Department||Southern University of Science and Technology|
1.Guangdong University of Petrochemical Technology,Maoming,Guangdong,525000,China
2.South University of Science and Technology of China,Shenzhen,Guangdong,518000,China
Tang，Yingting,Zhu，Qiang. PE Classroom Teaching Innovation Based on Deep Learning from the Perspective of New Curriculum Standard[J]. WIRELESS COMMUNICATIONS & MOBILE COMPUTING,2022,2022.
Tang，Yingting,&Zhu，Qiang.(2022).PE Classroom Teaching Innovation Based on Deep Learning from the Perspective of New Curriculum Standard.WIRELESS COMMUNICATIONS & MOBILE COMPUTING,2022.
Tang，Yingting,et al."PE Classroom Teaching Innovation Based on Deep Learning from the Perspective of New Curriculum Standard".WIRELESS COMMUNICATIONS & MOBILE COMPUTING 2022(2022).
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