- Research Article
- 10.54254/2755-2721/2026.31260
Design and Classroom Application of Real-Time Evaluation Algorithm for Gymnastics Movements in Colleges and Universities Based on Lightweight Convolutional Neural Network
- Jan 20, 2026
- Applied and Computational Engineering
- Jinghui Zhou + 1 more +1
Against the backdrop of the advancement of educational digitalization, smart sports have become the core direction of physical education teaching reform in colleges and universities. However, the evaluation of gymnastics teaching in colleges and universities is deeply trapped in the traditional model and disconnected from the trend of precise quantification. This paper integrates video stream recognition, skeleton key point evaluation and lightweight CNN technology to design a real-time evaluation algorithm suitable for classroom scenarios. Verified by 12,000 gymnastic movement samples, this algorithm achieves a balance between lightweight and precision, providing technical support for the data-driven transformation of gymnastic teaching.
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