Artificial Intelligence Auxiliary Algorithm for Wushu Routine Competition Decision Based on Feature Fusion

The developments of modern science and technology have significantly promoted the progress of sports science. Advanced technological methods have been widely used in sports training, which has not only improved the scientific level of training but also promoted the continuous growth of sports techno...

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Main Authors: Chao Zhao, Bing Li
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Journal of Healthcare Engineering
Online Access:http://dx.doi.org/10.1155/2021/1632393
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spelling doaj-5cbc0ceebc324624a84cf06efac5210e2021-08-23T01:33:15ZengHindawi LimitedJournal of Healthcare Engineering2040-23092021-01-01202110.1155/2021/1632393Artificial Intelligence Auxiliary Algorithm for Wushu Routine Competition Decision Based on Feature FusionChao Zhao0Bing Li1Wushu College WuHan Sports UniversityYong in Univerity KoreaThe developments of modern science and technology have significantly promoted the progress of sports science. Advanced technological methods have been widely used in sports training, which has not only improved the scientific level of training but also promoted the continuous growth of sports technology and competition results. Competitive Wushu routine is an important part of Chinese Wushu. The development trend of competitive Wushu routine affects the development of the whole Wushu movement. To improve the training effect of the Wushu routine using artificial intelligence, this paper employed fuzzy information processing and feature extraction technology to analyze the visual features in the process of Wushu competition. The deep neural network-based region segmentation method was employed for implicit feature extraction to examine the shape, texture, and other image features of Wushu routines and improve the recognition performance. The proposed feature extraction model achieved the highest average accuracy of 93.98% accuracy as compared to other contemporary algorithms. Finally, the model was evaluated to validate the superior performance of the proposed method in improving the decision-making ability and effective instruction ability of the martial arts routine competition.http://dx.doi.org/10.1155/2021/1632393
collection DOAJ
language English
format Article
sources DOAJ
author Chao Zhao
Bing Li
spellingShingle Chao Zhao
Bing Li
Artificial Intelligence Auxiliary Algorithm for Wushu Routine Competition Decision Based on Feature Fusion
Journal of Healthcare Engineering
author_facet Chao Zhao
Bing Li
author_sort Chao Zhao
title Artificial Intelligence Auxiliary Algorithm for Wushu Routine Competition Decision Based on Feature Fusion
title_short Artificial Intelligence Auxiliary Algorithm for Wushu Routine Competition Decision Based on Feature Fusion
title_full Artificial Intelligence Auxiliary Algorithm for Wushu Routine Competition Decision Based on Feature Fusion
title_fullStr Artificial Intelligence Auxiliary Algorithm for Wushu Routine Competition Decision Based on Feature Fusion
title_full_unstemmed Artificial Intelligence Auxiliary Algorithm for Wushu Routine Competition Decision Based on Feature Fusion
title_sort artificial intelligence auxiliary algorithm for wushu routine competition decision based on feature fusion
publisher Hindawi Limited
series Journal of Healthcare Engineering
issn 2040-2309
publishDate 2021-01-01
description The developments of modern science and technology have significantly promoted the progress of sports science. Advanced technological methods have been widely used in sports training, which has not only improved the scientific level of training but also promoted the continuous growth of sports technology and competition results. Competitive Wushu routine is an important part of Chinese Wushu. The development trend of competitive Wushu routine affects the development of the whole Wushu movement. To improve the training effect of the Wushu routine using artificial intelligence, this paper employed fuzzy information processing and feature extraction technology to analyze the visual features in the process of Wushu competition. The deep neural network-based region segmentation method was employed for implicit feature extraction to examine the shape, texture, and other image features of Wushu routines and improve the recognition performance. The proposed feature extraction model achieved the highest average accuracy of 93.98% accuracy as compared to other contemporary algorithms. Finally, the model was evaluated to validate the superior performance of the proposed method in improving the decision-making ability and effective instruction ability of the martial arts routine competition.
url http://dx.doi.org/10.1155/2021/1632393
work_keys_str_mv AT chaozhao artificialintelligenceauxiliaryalgorithmforwushuroutinecompetitiondecisionbasedonfeaturefusion
AT bingli artificialintelligenceauxiliaryalgorithmforwushuroutinecompetitiondecisionbasedonfeaturefusion
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