RETRACTED ARTICLE: Automatic detection technology for sports players based on image recognition technology: the significance of big data technology in China’s sports field

Li, Hongge; Manickam, Adhiyaman; Samuel, R. Dinesh Jackson

doi:10.1007/s10479-021-04409-1

Cited by 10 publications

(7 citation statements)

References 36 publications

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“…However, the ideological field also needs attention similar to learning, so this study uses the Apriori algorithm to establish a teaching effect prediction model, aiming to broaden students' ideological horizons and strengthen their political beliefs. It not only enables college students to make great progress in their academic performance [18]. And finally, the prediction model established by this research can become a magic weapon.…”

Section: Introductionmentioning

confidence: 91%

The Construction of a Prediction Model for the Teaching Effect of Two Courses Education in Colleges and Universities Based on Machine Learning Algorithms

Pei

2022

Wireless Communications and Mobile Computing

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In this era of machine learning being applied to various fields, its use in college Two courses education has gradually become the next outlet. The reform and innovation based on machine learning is an upgrade that must be carried out in Two courses education. In this experiment, the purpose of predicting the effect of Two courses classroom teaching is achieved by rationally using the Apriori algorithm in the machine learning algorithm to construct a prediction model. After modeling and verification, it has been shown the prediction model of Two courses classroom and extracurricular teaching effect using the machine. Apriori algorithm technology can enhance the participation and interaction of Two courses education, stimulate the interest of college students in Two courses education, and improve their enthusiasm. The selection and basic information of Apriori algorithm and the prediction for practical application have been studied. The accuracy of the prediction model is investigated. Compared with the logistic regression algorithm, it is concluded that the model established by the Apriori algorithm selected in this experiment has higher accuracy. Finally, the prediction model is organically integrated into the Two courses of a university carefully selected by the experiment. After a semester of intensive use, and then algorithm effects, the difference in accuracy is no more than 2%, far better than the expected 6%.

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Section: Introductionmentioning

confidence: 91%

The Construction of a Prediction Model for the Teaching Effect of Two Courses Education in Colleges and Universities Based on Machine Learning Algorithms

Pei

2022

Wireless Communications and Mobile Computing

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“…Third, face recognition, infrared sensors, cameras, and other technical means help to understand students' sports behavior; infer students' needs through students' sports behavior data; and provide data support for students' personalized sports suggestions and services. In addition, through augmented reality, virtual reality, and other technical means, students can also have virtual and intelligent space service experiences of virtual and real integration ( 20 ).…”

Section: Resultsmentioning

confidence: 99%

Big data-driven intelligent governance of college students' physical health: System and strategy

Deng

Luo

et al. 2022

Front. Public Health

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With the development of information technology, the application of a new generation of information technologies, such as big data, Internet Plus, and artificial intelligence, in the sports field is an emerging, novel trend. This paper examined the relevant research results and literature on physical education, computer science, pedagogy, management, and other disciplines, then used a self-made questionnaire to investigate the physical health status of Chinese college students. The big data were subsequently analyzed, which provided a scientific basis for the construction of an intelligent governance system for college students' physical health. Intelligent devices may be used to obtain big data resources, master the physical sports development and psychological status of college students, and push personalized sports prescriptions to solve the problems existing in college students' physical health. Research shows that there are four reasons for the continuous decline in Chinese college students' physical health levels. These are students' lack of positive exercise consciousness and healthy sports values (85.43%), a weak family sports concept and lack of physical exercise habits (62.76%), poor implementation of school sports policies (55.35%), and people's distorted sports value orientation (42.27%). Through the connecting effect of data, we can bring together the positive role of the government, school, society, family, and students so as to create an interlinked impact to promote students' physical health. The problems of insufficient platform utilization, lack of teaching resources, lagging research, and insufficient combination with big data in the intelligent governance of physical health of Chinese college students can be solved by building an intelligent governance system of physical health. Such a system would be composed of school infrastructure, data resources and technology processing, and intelligent service applications. Among these, school infrastructure refers to the material foundation and technical support. The material foundation includes perceptions, storage, computing, networks, and other equipment, and the technical support includes cloud computing, mobile Internet, the Internet of Things, artificial intelligence, and deep learning. Data resources refer to smart data, such as stadium data, physical health management data, and students' sports behavior data, which are mined from data resources such as students' physical development, physical health, and sports through big data technology and intelligent wearable devices. Intelligent managers provide efficient, intelligent, accurate, and personalized intelligent sports services for college students through data resource value mining, venue space-time optimization, health knowledge discovery, sports prescription pushes, etc. Finally, we put forward the development strategy for further deepening and improving the big data-driven intelligent governance system for college students' physical health. The intelligent governance system of physical health driven by big data and its development strategy can not only accurately guide and improve the physical health level of college students but also realize integrated teaching inside and outside physical education classes.

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“…According to Li et al [7], image segmentation using the AL algorithm was used to investigate if image recognition science might be applied to athletes in this article (IPAIT). Results show that compared to previous models, the suggested IPAIT model improves recognition by 98.08 percent, an outcome rate of 97.07 percent, and an accuracy ratio of 95.9.percent [7].…”

Section: Literature Surveymentioning

confidence: 99%

Design and Implementation of Intelligent Analysis Technology in Sports Video Target and Trajectory Tracking Algorithm

Yang

Wang

2022

Wireless Communications and Mobile Computing

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The object tracking is an important task to future generations to find accurate information from frame (sports or any cctv). The available models like RFO, DT, Xboosting, Gradient boosting, and CNN are outdated for sports video tracking using video. The target and trajectory finding are very important for accurate tracking. Therefore, for crossover, the above limitation’s intelligence analysis is performed with ANN. The video tracking can be very simple and efficient with proposed model. As a result, this ANN offers a sports camera target detection system based on an upgraded grey neural network. This research uses the automatic threshold technique to divide the target object of sports camera and derive the designated target of sports video based on the pixel grey difference of the target image in sports video. The moving objects are tracked by the object tracking algorithm, and features are extracted to obtain the results. The performance measures like accuracy of 95.23%, sensitivity of 94.45%, and recall of 93.34% had been attained.

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RETRACTED ARTICLE: Automatic detection technology for sports players based on image recognition technology: the significance of big data technology in China’s sports field

Cited by 10 publications

References 36 publications

The Construction of a Prediction Model for the Teaching Effect of Two Courses Education in Colleges and Universities Based on Machine Learning Algorithms

The Construction of a Prediction Model for the Teaching Effect of Two Courses Education in Colleges and Universities Based on Machine Learning Algorithms

Big data-driven intelligent governance of college students' physical health: System and strategy

Design and Implementation of Intelligent Analysis Technology in Sports Video Target and Trajectory Tracking Algorithm

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