3d Convolutional Neural Network for View Classification of Stress Echo Videos

Aly, Yousof H.; Jain, Vaibhav; Attia, Zachi I.; Pellikka, Patricia A.

doi:10.1016/s0735-1097(21)02642-5

Cited by 1 publication

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“…In the game, this information can be used to formulate corresponding tactics according to the opponent's technical characteristics and sports habits. However, the traditional technical and tactical analysis method is obtained by manually watching a large number of training and competition videos, which has problems such as high labor cost, serious data loss, long delay, and low accuracy, which also restrict the technical and tactical intelligence analysis work [1][2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Video Tactical Intelligence Analysis Method of Karate Competition Based on Convolutional Neural Network

Zhong

2022

Discrete Dynamics in Nature and Society

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The performance of image classification technology based on deep network has been greatly improved, making computer vision enter the stage of industrialization and be gradually applied to many aspects of human work and life. As a typical classification task in computer vision, human behavior recognition has immeasurable potential value in medical, family, transportation, and other scenarios. At the same time, in the field of competitive sports, the integration of artificial intelligence technology and sports technical and tactical analysis is undoubtedly an important way to innovate and improve the technical and tactical level. Taking karate as an example, the study of athletes’ training and competition videos is an important means and method for technical and tactical analysis in competitive sports. Traditional tactical intelligence analysis methods have many shortcomings, such as high labor cost, serious data loss, long delay, and low accuracy. Therefore, based on the convolutional neural network, this paper establishes a new graph convolution model for automatic intelligent analysis of karate athletes’ technical action recognition, action frequency statistics, and trajectory tracking. The technology effectively makes up for the disadvantages of traditional tactical intelligence analysis methods. The research results show that the new topology map construction method has a significant effect on improving the accuracy of behavior recognition and also lays a foundation for technical and tactical analysis.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Video Tactical Intelligence Analysis Method of Karate Competition Based on Convolutional Neural Network

Zhong

2022

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

show abstract

3d Convolutional Neural Network for View Classification of Stress Echo Videos

Cited by 1 publication

References 0 publications

[Retracted] Video Tactical Intelligence Analysis Method of Karate Competition Based on Convolutional Neural Network

[Retracted] Video Tactical Intelligence Analysis Method of Karate Competition Based on Convolutional Neural Network

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