Abstract
Based on 549 literatures with the theme of “sports artificial intelligence” and other keywords in web of science database since 1995, this paper uses CiteSpace V software for visualization processing and analysis, and combs the country, discipline distribution, research hotspots and evolution trend of sports artificial intelligence research in recent 25 years by means of visual knowledge mapping, and discusses its research progress and development direction. 1) The research area of sports artificial intelligence is widely distributed, among which the United States, China and Germany are in the leading position. 2) Sports artificial intelligence research involves many disciplines, mainly using and learning from the research methods and theoretical perspectives of computer science, engineering, sports science and other disciplines. 3) The frequency and centrality of keywords confirm that machine learning is the main direction in the field of sports artificial intelligence, artificial neural network is the main algorithm, and data mining is the basis of practice and research. 4) Research hotspots include simple activity recognition and energy consumption research based on wearable accelerometer technology; action analysis and damage prevention and control research based on wearable sensor; computer vision scene classification research based on convolution neural network algorithm; analysis and prediction of physical fitness and technology and tactics based on computer vision; human posture recognition technology based on computer Deep learning.
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Yuan, J. (2023). Clustering and Evolution of International Sports Field Based on Multi-sensor Fusion Technology. In: Ahmad, I., Ye, J., Liu, W. (eds) The 2021 International Conference on Smart Technologies and Systems for Internet of Things. STSIoT 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 122. Springer, Singapore. https://doi.org/10.1007/978-981-19-3632-6_89
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DOI: https://doi.org/10.1007/978-981-19-3632-6_89
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