An Online Arrangement Method of Difficult Actions in Competitive Aerobics Based on Multimedia Technology

Li, Li

doi:10.1155/2021/9968401

Cited by 5 publications

(4 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In 1949, psychologist Bai et al established the first rule of self-organizing learning, Hebbian learning, pointing out that when two neurons are excited at the same time, the strength of connection weight increases [ 6 ]. In 1954, Li first simulated the Hebbian network with a computer at MIT [ 7 ]. In 1958, Persiyanova-Dubrova et al proposed the perceptron model 1% (perceptron model)—the well-known single-layer neural network model (the input layer is not included in the network layer measurement) is the first real artificial neural network model—and then proposed a two-layer neural network model with a hidden layer [ 8 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Comparative Study on the Effect of Various Aerobic Exercises on College Students’ Weight Loss Based on Deep Learning Analysis

Huang

Luo

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

In order to solve the problem of higher obesity rate of college students and meet the needs of college students to lose weight effectively, a comparative study on the effect of various aerobic exercises on college students’ weight loss based on in-depth learning analysis is proposed. The experiment shows that 30 subjects who voluntarily participated in the weight loss experiment and research were selected from a university, including 16 men and 14 women. It shows that aerobic exercise plays an important role in improving people’s energy metabolism. Based on the deep unsupervised learning algorithm, this paper studies the effect of a variety of aerobic exercises on college students’ weight loss. It is found that visceral fat obese people are easier to lose weight than outer skin fat obese people. With the help of aerobic exercise to lose weight, we should choose the aerobic exercise items significantly increased in EPOC during exercise recovery according to the obesity characteristics and types of different college students so that the effect of exercise weight loss is more effective.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Comparative Study on the Effect of Various Aerobic Exercises on College Students’ Weight Loss Based on Deep Learning Analysis

Huang

Luo

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…Aiming at the development trend of the choreography structure of competitive aerobics, Li studied the online choreography method of difficult movements of competitive aerobics based on multimedia technology to improve the choreography effect. In the competitive aerobics video based on top-down feature fusion, RGB image, optical flow image, and corrected optical flow image were used as the input mode of difficult action recognition network [2]. Yan proved the inevitability of applying multimedia technology in college basketball teaching and the feasibility of implementing multimedia physical education from three universities and colleges and analyzed the factors that affected the impact of multimediaassisted teaching from various aspects of the multimedia teaching environment and teachers' teaching ability [3].…”

Section: Related Workmentioning

confidence: 99%

Application of Multimedia Technology in Online Piano Teaching

Ding

Huang

2022

Mobile Information Systems

View full text Add to dashboard Cite

Multimedia teaching has the characteristics of flexibility, nonlinear structure, and the combination of multiple senses, which can fully mobilize the enthusiasm and initiative of students. Because the traditional piano teaching method is too old-fashioned and single, which is not conducive to stimulating students’ interest in learning, the piano teaching is studied according to the methods of information technology, online education, and mixed teaching. This paper controls the rhythm of teaching through multimedia teaching technology, stimulates students’ thirst for knowledge, and uses multimedia technology to enrich piano teaching resources to meet teaching needs. Then, by means of a questionnaire, the attitude of most of the high-efficiency students towards online piano teaching with multimedia technology is understood. At the same time, the cluster analysis system is used to analyze the online public opinion evaluation of the three teaching methods by collecting the network behavior of users in various distribution platforms on the Internet and analyzing the feature vector according to the function space formed by the relevant evaluation indicators. The accuracy of the system is above 82%, so the teaching evaluation is effective. Through the value evaluation model of the system, user dynamics can be accurately understood and applied to other fields.

show abstract

“…The movement recognition of aerobics provides effective help for accurate learning of aerobics and time love you. In addition, the motion recognition for aerobics has broad application prospects in education, sports rehabilitation, and personal fitness [4][5]. However, due to the complexity and diversity of aerobics movements, there are still many difficulties in using computers to achieve high-precision recognition of these movements.…”

Section: Introductionmentioning

confidence: 99%

The Recognition of Aerobics Movements Using Bone Data Combined with ST-GCN

Yang,

Zhao,

Xia

2024

SCPE

View full text Add to dashboard Cite

To solve the aerobics action recognition and promote the gradual intelligence and standardization of aerobics teaching and evaluation, a network model based on spatial temporal graph convolution and combined with attention mechanism was proposed. This model improved the extraction efficiency of spatiotemporal features and channel features by introducing spatiotemporal graph and channel attention mechanisms, respectively, thereby improving the accuracy of action recognition. And a time extension module was introduced into each basic module, and additional features between adjacent vertices were extracted by extending the time graph between frames. These experiments confirmed that this model exhibited high accuracy in identifying aerobics movements. The recognition accuracy of basic actions was above 93.6%, and the recognition accuracy of two actions had reached 98.4% and 98.6% respectively. For advanced actions, the recognition accuracy of the model had slightly decreased, but the average value was still above 95%. The accuracy of difficult motion recognition had also achieved good results, reaching a maximum of 94.5%. These data indicate that this model can achieve high accuracy in handling action recognition tasks of different difficulty levels, and can identify aerobics movements of different difficulty levels.

show abstract

An Online Arrangement Method of Difficult Actions in Competitive Aerobics Based on Multimedia Technology

Cited by 5 publications

References 26 publications

Comparative Study on the Effect of Various Aerobic Exercises on College Students’ Weight Loss Based on Deep Learning Analysis

Comparative Study on the Effect of Various Aerobic Exercises on College Students’ Weight Loss Based on Deep Learning Analysis

Application of Multimedia Technology in Online Piano Teaching

The Recognition of Aerobics Movements Using Bone Data Combined with ST-GCN

Contact Info

Product

Resources

About