Research and Analysis on the Aesthetics of Folk Dance Based on the Background of Big Data

DOI

10.2991/978-94-6463-238-5_71How to use a DOI?

Keywords

Convolutional Neural Networks; Four Segment Teaching Method; Instructional Design; Secondary School Dance Teaching

Abstract

This paper analyzes a secondary school dance teaching example based on the theory of “four-stage teaching method”, which enriches the teaching content and explores the depth of knowledge by constructing knowledge links and using multimedia-assisted teaching; it adopts a combination of words, paintings and dances to refine the action elements and broaden the latitude of knowledge; it integrates the commonality of “four-stage teaching method” with the characteristics of dance, and explores a new method of secondary school dance teaching from the perspective of improving teaching efficiency and enhancing students’ learning quality, so as to make the teaching interlocked and guide students to help each other teach and express their emotions freely, so as to apply what they have learned. The “four-stage teaching method” applied to secondary school dance teaching strengthens secondary school students’ self-efficacy beliefs, enhances their sense of autonomy and competence, improves their learning efficiency, and promotes their overall development. In recent years, with the breakthrough development of computer technology, computer-aided diagnosis has made rapid progress in the field of medical image processing, and it has played an important role in improving work efficiency and reducing missed diagnoses. Meanwhile, convolutional neural networks have been widely used in the field of image processing because of their good self-learning ability and prediction capability. To address the above problems, this paper proposes a computer-aided diagnosis method for meniscus using convolutional neural networks to help doctors make fast and accurate decisions using MRI images of patients’ knee joints provided by the First Affiliated Hospital of Anhui Medical University.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Tianjuan Yang
AU  - Md. Jais Ismail
PY  - 2023
DA  - 2023/09/26
TI  - Research and Analysis on the Aesthetics of Folk Dance Based on the Background of Big Data
BT  - Proceedings of the 2023 4th International Conference on Big Data and Informatization Education (ICBDIE 2023)
PB  - Atlantis Press
SP  - 507
EP  - 514
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-238-5_71
DO  - 10.2991/978-94-6463-238-5_71
ID  - Yang2023
ER  -