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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2021-01-01
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Series: | Journal of Healthcare Engineering |
Online Access: | http://dx.doi.org/10.1155/2021/1632393 |
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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 |
_version_ |
1721198863859056640 |