Automatic Knee Injury Identification through Thermal Image Processing and Convolutional Neural Networks

Trejo-Chavez, Omar; Amezquita-Sanchez, Juan P.; Huerta-Rosales, Jose R.; Morales-Hernandez, Luis A.; Cruz-Albarran, Irving A.; Valtierra-Rodríguez, Martín

doi:10.3390/electronics11233987

Cited by 3 publications

(1 citation statement)

References 46 publications

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“…Previous research has primarily focused on specific sports or injury sites. Notably, studies on knee injuries achieved high accuracy (98.32%) using infrared thermography and convolutional neural networks [10]. Another investigation centred on head injuries during the Beijing 2022 Winter Olympics, proposing automated identification methods and treatment strategies [11].…”

Section: Literature Reviewmentioning

confidence: 99%

Predicting Player’s Healthiness Using Machine Learning

K.V.S,

K.M.N,

M.D.S.U

et al. 2023

IRJIET

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This research paper introduces the PHD (Player Health Detection) system as a solution to address the issue of inadequate health checking of players prior to sports events. The PHD system, utilize real-time image and video processing technology, to detect players' health conditions and prioritize their safety and well-being. The system incorporates analysis of body balance, injury detection, exercise video analysis, and heart rate measurement to evaluate player eligibility for sports events. For this specific purpose, we have created a mobile application by integrating computer vision technology and employing specialized image processing software. The anticipated outcomes of this solution include injury prevention, enhanced player safety, and informed decision-making for coaches regarding player participation. The implementation of the PHD system contributes to the advancement of the sports industry by creating a safer environment and actively supporting the health and wellbeing of players.

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Section: Literature Reviewmentioning

confidence: 99%

Predicting Player’s Healthiness Using Machine Learning

K.V.S,

K.M.N,

M.D.S.U

et al. 2023

IRJIET

View full text Add to dashboard Cite

show abstract

A new deep learning based end-to-end pipeline for hamstring injury detection in thermal images of professional football player

Ergene,

Bayrak,

Ceylan

2024

Quantitative InfraRed Thermography Journal

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Research on Building a New Mode of Civic and Political Education by Image Recognition Technology for Popularizing Socialist Core Values

Liu

2024

Applied Mathematics and Nonlinear Sciences

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Given the current state of ideological education in colleges and universities, we propose leveraging image recognition technology to foster innovation and digital advancement in this mode of education. The weighted average method is used to greyscale the video images of students’ classrooms, and after binarizing the images using the OTSU algorithm, interference factors are avoided by denoising and angle correction. We combine the motion history image (MHI) and HOG features to create a new feature that depicts Civics classroom behavior. The SVM classifier then performs the classification of classroom behavior, ultimately constructing the Civics classroom behavior recognition model based on HOC+MHII+SVM. This paper’s model and research data are combined to conduct an example analysis of Civics education in colleges and universities. It can be concluded from the analysis that, in the case of simultaneously adopting SVM for recognition and classification, it is found that HOC+MHI feature fusion has a more significant effect on classroom behavior recognition than FPN+Multi-layer CBAM, and the difference of its various indexes is maintained within the range of 0.01~0.08. In addition, the experimental group has a significant difference relationship in the four dimensions of demonstrating the concept of honor and shame, the concept of national development, the value of development, and the value of society, P<0.05. This study provides theoretical references for research on the innovation of the ideological and political education model and is conducive to the promotion of cultivating the formation of students’ socialist core values.

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Automatic Knee Injury Identification through Thermal Image Processing and Convolutional Neural Networks

Cited by 3 publications

References 46 publications

Predicting Player’s Healthiness Using Machine Learning

Predicting Player’s Healthiness Using Machine Learning

A new deep learning based end-to-end pipeline for hamstring injury detection in thermal images of professional football player

Research on Building a New Mode of Civic and Political Education by Image Recognition Technology for Popularizing Socialist Core Values

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