Physical Education Teacher’s Training in Swimming under the Joint Didactic Action

Sghaier, Donia; Elandoulsi, Souha; Mami, Mohamed; Bouassida, Anissa

doi:10.4236/ce.2015.622250

Cited by 17 publications

(3 citation statements)

References 2 publications

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“…Literature [ 16 ] analyzes the development and improvement of the sports culture creative industry and draws the feasibility of the development of the sports culture creative industry. Paper [ 17 ] pointed out that the development and improvement of the sports cultural creative industry will directly affect the sustainable development of the sports industry. By analyzing the feasibility of the development of the sports cultural creative industry, it summarizes the main problems in the current development of the sports cultural creative industry and puts forward recommendations accordingly.…”

Section: Related Workmentioning

confidence: 99%

Research on the Development of Digital Creative Sports Industry Based on Deep Learning

Chen

2022

Computational Intelligence and Neuroscience

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The core of the digital entrepreneurial sports culture creative industry lies in innovation, which emphasizes the new impetus brought by the digital entrepreneurial sports culture to the social economy. The digital entrepreneurial sports cultural creative industry is rooted in the cultural creative industry. The digital entrepreneurial sports cultural creative industry is also an important part of the sports industry, and its development highly depends on the development of the sports industry. The digital entrepreneurial sports cultural creative industry has the characteristics of both the sports industry and the cultural creative industry. This paper uses the deep learning technology to study the development of the digital creative sports industry and build an intelligent model. Moreover, this paper assigns weights to the input multidimensional features, extracts the most relevant data features, and analyzes the performance of the proposed model through simulation experiments. From the experimental analysis results, we can see that the model proposed in this paper has certain practicality.

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Section: Related Workmentioning

confidence: 99%

Research on the Development of Digital Creative Sports Industry Based on Deep Learning

Chen

2022

Computational Intelligence and Neuroscience

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“…It can be understood as the result of weighting and normalizing multiple virtual forces with Gaussian functions. Moreover, it is also equivalent to performing Gaussian coding on this behavior [25]. Due to the time dependency between the Internet of Health ings systems, it is not allowed to directly couple with other dynamic Internet of Health ings systems and cannot be decoupled, which will cause the Internet of Health ings system to be inflexible and changeable.…”

Section: Dynamic Motion Primitive Algorithm Based On the Coupling Of Sole Pressurementioning

confidence: 99%

Athlete Rehabilitation Evaluation System Based on Internet of Health Things and Human Gait Analysis Algorithm

Lian-zhen

Zhu

2021

Complexity

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In order to improve the effect of athlete’s injury recognition and rehabilitation evaluation, this paper studies the traditional rehabilitation evaluation method and proposes a new athlete rehabilitation evaluation system combining the Internet of Health Things technology and human gait analysis algorithm. Moreover, this paper combines sports characteristics to improve the algorithm of human gait analysis. In addition, through the study of the athlete’s human body modeling and movement process, a human gait analysis algorithm that can be applied to multiple sports is proposed, and the gait parameter analysis and algorithm reliability research are carried out through simulation analysis. After confirming that the algorithm is effective, this paper combines the Internet of Health Things technology to construct a system model, obtains the system function module architecture with the support of the Internet of Health Things technology, and conducts experiments to verify the system performance. From the experimental research, it can be seen that the model constructed in this paper meets the theoretical and practical needs, and the system in this paper can be applied to practice in the future. The human gait recognition algorithm constructed in this article has a good effect and can play an important role in sports rehabilitation of athletes. At the same time, the system constructed in this article has certain advantages over traditional sports rehabilitation systems with the support of algorithms.

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“…At the same time, it recommends that players strengthen their physical fitness while learning to use the two-handed backhand technique, and continuously improve their tennis IQ, so that they can master the technique more quickly and promote the popularization of tennis. e literature [15] divided the technique of receiving and serving into two sections in the research of receiving and serving tennis. Among them, one is the front section of the shot, and the other is the shot section.…”

Section: Related Workmentioning

confidence: 99%

Analysis Technology of Tennis Sports Match Based on Data Mining and Image Feature Retrieval

Hong

Deng

2020

Complexity

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Tennis game technical analysis is affected by factors such as complex background and on-site noise, which will lead to certain deviations in the results, and it is difficult to obtain scientific and effective tennis technical training strategies through a few game videos. In order to improve the performance of tennis game technical analysis, based on machine learning algorithms, this paper combines image analysis to identify athletes’ movement characteristics and image feature recognition processing with image recognition technology, realizes real-time tracking of athletes’ dynamic characteristics, and records technical characteristics. Moreover, this paper combines data mining technology to obtain effective data from massive video and image data, uses mathematical statistics and data mining technology for data processing, and scientifically analyzes tennis game technology with the support of ergonomics. In addition, this paper designs a controlled experiment to verify the technical analysis effect of the tennis match and the performance of the model itself. The research results show that the model constructed in this paper has certain practical effects and can be applied to actual competitions.

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Physical Education Teacher’s Training in Swimming under the Joint Didactic Action

Cited by 17 publications

References 2 publications

Research on the Development of Digital Creative Sports Industry Based on Deep Learning

Research on the Development of Digital Creative Sports Industry Based on Deep Learning

Athlete Rehabilitation Evaluation System Based on Internet of Health Things and Human Gait Analysis Algorithm

Analysis Technology of Tennis Sports Match Based on Data Mining and Image Feature Retrieval

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