ArticleComputational intelligence and neuroscience2022
Automatic Arrangement of Sports Dance Movement Based on Deep Learning.
Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- A deep reinforcement learning approach to dance movement analysis.Scientific reports · 2026Article
- Hybrid model integrating LeViT transformer and distillation techniques for pattern detection and dance classification.Scientific reports · 2025Article
- The use of artificial intelligence-based Siamese neural network in personalized guidance for sports dance teaching.Scientific reports · 2025Article
- Experimental effects of multi-dance sport training on student performance: a dual analysis of physical fitness and aesthetic skill development.Frontiers in psychology · 2025Article
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Authors and funding
3 authors.
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Abstract
Sports dance is a new form of sports that integrates sports, dance, music, and other elements. The core content of "dance" is an important carrier for athletes to display their body art. This article aims to study the automatic arrangement of sports dance based on deep learning. This article first introduces the development process of deep learning. As the latest research direction developed from artificial neural network technology in machine learning, deep learning has attracted widespread attention from the society. And then proposing a shallow regression model based on deep learning, a convolutional neural network based on deep learning, and an offline sorting regression model, given the general process of deep learning, then, based on the clustering algorithm, the deep learning was researched, and the sport dance movement arrangement was analyzed based on the deep learning. The experimental results of this article show that deep learning can effectively enhance the artistic ability of automatic choreography in sports dance and increase the accuracy of dance movements by 80%. At the same time, on the basis of deep learning, the practical ability is strengthened on the basis of consolidating theory, to further improve one's own business ability and educational technology level, actively absorb advanced teaching methods, and earnestly delve into reasonable teaching methods. It is also used in curriculum training practice to actively gain insight into new development trends in educational methods and skills, to enhance the artistic creativity of students' arrangements.
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Registered trials
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