牡丹江师范学院学报（自然科学版）Issue(2)：50-56,7.
基于深度学习的羽毛球正手高远球动作标准智能评估方法
An Intelligent Evaluation Method for the Standard of Forehand High and Far Shots in Badminton based on Deep Learning
摘要
Abstract
Propose a deep learning based intelligent evaluation method for high and far ball movements of badmin-ton forehand(DL-BEFBFS).Input image data samples into an improved convolutional neural network,extract spa-tiotemporal features of badminton movements,and obtain intelligent recognition results of badminton forehand move-ments;Using the spatiotemporal characteristics of actions to calculate intelligent evaluation indicators such as frame height matching degree and center of gravity stability index;Assign weights to indicators based on their contribu-tion,and use principal component analysis to achieve intelligent evaluation of badminton forehand high and far ball action standards.The experimental results show that the action level evaluation accuracy of the DL-BEFBFS method is 0.97,which is 0.075 higher than traditional evaluation methods and has better evaluation performance.关键词
深度学习算法/羽毛球动作/智能评估Key words
deep learning algorithm b/adminton moves/intelligent assessment分类
信息技术与安全科学引用本文复制引用
童川..基于深度学习的羽毛球正手高远球动作标准智能评估方法[J].牡丹江师范学院学报（自然科学版）,2026,(2):50-56,7.基金项目
2023年安徽省高等学校省级质量工程项目(2023cxtd234) （2023cxtd234）
