中文版 | English
Title

PE Classroom Teaching Innovation Based on Deep Learning from the Perspective of New Curriculum Standard

Author
Corresponding AuthorTang,Yingting
Publication Years
2022
DOI
Source Title
ISSN
1530-8669
EISSN
1530-8677
Volume2022
Abstract
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.
URL[Source Record]
Indexed By
SCI ; EI
Language
English
SUSTech Authorship
Others
WOS Research Area
Computer Science ; Engineering ; Telecommunications
WOS Subject
Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS Accession No
WOS:000859442300008
Publisher
EI Accession Number
20223812751038
EI Keywords
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
COMPUTER SCIENCE
Scopus EID
2-s2.0-85137856530
Data Source
Scopus
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/402411
DepartmentSouthern University of Science and Technology
Affiliation
1.Guangdong University of Petrochemical Technology,Maoming,Guangdong,525000,China
2.South University of Science and Technology of China,Shenzhen,Guangdong,518000,China
Recommended Citation
GB/T 7714
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.
APA
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.
MLA
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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