理解力
感知
深度学习
优势和劣势
计算机科学
人工智能
数据科学
点(几何)
机器学习
心理学
数学
几何学
社会心理学
神经科学
程序设计语言
作者
Zhonghan Zhao,Wenhao Chai,Shengyu Hao,Wenhao Hu,Guanhong Wang,Shidong Cao,Mingli Song,Jenq–Neng Hwang,Gaoang Wang
标识
DOI:10.48550/arxiv.2307.03353
摘要
Deep learning has the potential to revolutionize sports performance, with applications ranging from perception and comprehension to decision. This paper presents a comprehensive survey of deep learning in sports performance, focusing on three main aspects: algorithms, datasets and virtual environments, and challenges. Firstly, we discuss the hierarchical structure of deep learning algorithms in sports performance which includes perception, comprehension and decision while comparing their strengths and weaknesses. Secondly, we list widely used existing datasets in sports and highlight their characteristics and limitations. Finally, we summarize current challenges and point out future trends of deep learning in sports. Our survey provides valuable reference material for researchers interested in deep learning in sports applications.
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