Deep Learning-Based Assessment of Sports-Assisted Teaching and Learning

Abstract

The current Internet development situation regarding the analysis of sports teaching information is very necessary and can be a way to improve the effectiveness of sports teaching in the information environment. Aiming at the defects of strong subjectivity and low discrimination accuracy of the current sports video classification results, this paper proposes an effective sports video classification method based on deep learning, which can effectively evaluate the sports assisted teaching. Specifically, the key frame features are obtained by using the similarity coefficient key frame extraction algorithm, and the sports video image classification is established through the deep learning coding model. Thus, the ability of the school to rely on the scheme proposed in this paper to improve the teaching facilities, physical education curriculum teaching materials, assessment teaching materials, management, and so on. The results show that for different types of sports videos, the overall effect of the classification of the method in the paper is significantly better than that of other current sports-assisted teaching evaluation methods, which has significantly improved the effect of sports-assisted teaching evaluation.