Identification of Sports Athletes’ High-Strength Sports Injuries Based on NMR

Zhou, Wenyong; Chu, Huan

doi:10.1155/2022/1016628

Cited by 4 publications

(3 citation statements)

References 22 publications

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“…In order to improve the accuracy of the defect detection, it is necessary to draw its contours. In this paper, mathematical morphology and adaptive thresholding methods will be used to create contours, and curves will be used to obtain broken contours [ 12 ]. The heavy injury contour design is a snake pattern that can receive the contour of the injured area.…”

Section: Methodsmentioning

confidence: 99%

High-Intensity Injury Recognition Pattern of Sports Athletes Based on the Deep Neural Network

Chen

Zhang

2022

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In order to solve the problem of low efficiency and accuracy of injury image recognition for sports athletes in high-intensity injury treatment, this paper proposes an injury recognition mode based on the deep neural network. In this paper, the image of sports injury is converted to gray level, and the contour of the injury part in the image is extracted according to the combination of adaptive thresholding and mathematical morphology. In this model, the seed points are selected, the active contour is used to approximate the initial contour, and the curve fitting method is used to fit the obtained discrete points to obtain the final damaged contour. The digital matrix is constructed by using the extracted number of pixels at the damaged position and relevant information. The images are arranged into feature vectors with a length of 64 according to the mode of column concatenation. The overall mean vector of the image is calculated. The calculation results, training samples, and image samples to be recognized are substituted into the Euclidean distance to obtain the preliminary recognition results of the damaged position of the image of sports injury. Then, the image segmentation is realized by clustering. The clustering segmentation results are used to color describe the pixel categories of the original image, calculate the relative damage proportion area in the sports injury image, and identify the damage parts of the high-intensity sports injury image. The experimental results show that the recognition rate of the neural network is 80%-100%, and the recognition time of this method is 0-0.6/s. The above method can improve the accuracy of the recognition of the damaged part of the sports injury image and shorten the recognition time and has certain feasibility in determining the sports injury part.

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Section: Methodsmentioning

confidence: 99%

High-Intensity Injury Recognition Pattern of Sports Athletes Based on the Deep Neural Network

Chen

Zhang

2022

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“…In this case, the optical flow field is zero. In Figure 5, the sphere does not move, but the light source is moving and the optical current moves on the surface of the object; the optical flow field in this case is not zero [14].…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

The Application and Development Trend of Youth Sports Simulation Based on Computer Vision

Zhou

Wang

2022

Wireless Communications and Mobile Computing

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Based on computer vision technology, this paper presents a human motion analysis and target tracking technology based on computer vision. In terms of moving target detection, the current moving target detection technology is summarized, and some experimental results of the algorithm are given. The background difference method under monocular camera is emphatically analyzed. The preliminary human contour is obtained by the background difference method. In order to obtain a smoother target contour, the mathematical morphology is used to remove the noise, and the judgment algorithm of the size of the image connected domain is added. A specific threshold is set to remove the connected domain of the noise block less than the threshold. In the aspect of human motion recognition, this paper selects human motion features, including minimum external rectangle aspect ratio, rectangularity, circularity, and moment invariant. The criteria for selecting human motion features are strong noise resistance and obvious distinction. Then, the three types of human motion images are classified and recognized. After cross-validation and parameter optimization, the recognition accuracy is significantly improved. The experimental results show that the video sequence collected in the field has a total of 376 frames, and the frame rate is 10 frames/s. Due to the small traffic, the mean shift algorithm based on adaptive feature fusion is used to track the target every 2-3 frames. And set the inverse X direction as the direction of entering the scene and the X direction as the direction of moving out of the scene so that the allowable error of the distance between the detection and tracking results is 10. The weight of each feature is dynamically updated by the similarity between the candidate model and the target model, which solves the problem that the mean shift algorithm is not robust enough when similar objects are occluded and interfered and achieves more accurate tracking.

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“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: Discrepancies in scope Discrepancies in the description of the research reported Discrepancies between the availability of data and the research described Inappropriate citations Incoherent, meaningless and/or irrelevant content included in the article Peer-review manipulation …”

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confidence: 99%

Retracted: Identification of Sports Athletes’ High-Strength Sports Injuries Based on NMR

2023

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Identification of Sports Athletes’ High-Strength Sports Injuries Based on NMR

Cited by 4 publications

References 22 publications

High-Intensity Injury Recognition Pattern of Sports Athletes Based on the Deep Neural Network

High-Intensity Injury Recognition Pattern of Sports Athletes Based on the Deep Neural Network

The Application and Development Trend of Youth Sports Simulation Based on Computer Vision

Retracted: Identification of Sports Athletes’ High-Strength Sports Injuries Based on NMR

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