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• W4304606998 abstract "Physical education is an important part of course teaching. Doing well in the teaching of this course can not only improve students’ quality, but also promote students’ healthy and all-round development. With the rapid development of China’s economy, leisure sports, as an important way of leisure life, are increasingly favored by people. However, the related leisure sports service talents and industrial management talents are in short supply, which has restricted the development of the leisure sports industry in breadth and depth. The demand in the leisure sports market for advanced applied talents has put forward the call of the times for the direction of running sports colleges and universities, which is also the significance of the study. To sum up, this paper builds a leisure physical education teaching model based on multisensor fusion. Firstly, it summarizes leisure sports and multisensor fusion technology and then introduces how to add multisensor technology to physical education teaching. Finally, some experiments are carried out using the data set published by the University of California. In the model training, the super parameters of the convolutional neural network with two to eight layers are tested. The experimental results verify the effectiveness of the model; it achieves an accuracy of 86% when the number of convolutional layers is 6. The connotation of sports leisure and entertainment and the content of talent training mode is clarified, which lays a theoretical foundation for the following research. Among them, the construction of a curriculum system is the core part of talent training measures, and it is also an important part of the construction of leisure sports specialty." @default.
• W4304606998 created "2022-10-12" @default.
• W4304606998 creator A5081656705 @default.
• W4304606998 date "2022-10-11" @default.
• W4304606998 modified "2023-10-18" @default.
• W4304606998 title "Construction of Leisure Physical Education Teaching Model Based on Multisensor Fusion" @default.
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• W4304606998 doi "https://doi.org/10.1155/2022/3656915" @default.
• W4304606998 hasPublicationYear "2022" @default.
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