| Autor: |
Pei Xiaopeng |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2444-8656 |
| DOI: |
10.2478/amns-2024-1870 |
| Popis: |
Based on the demand to adapt to the future development of education, the application of virtual reality technology in the field of education is becoming more and more extensive and in-depth. This paper applies virtual reality technology to art history teaching, constructs an art history teaching method using virtual reality technology, and designs a complete teaching process. The EEG signals of students in the teaching process are collected and pre-processed. The features in the EEG signals are extracted by using the SPCNN model with dual convolutional kernels in parallel. The EEG features are output through the convolutional layer and the all-connected hierarchy processing. A support vector machine calculated the maximum distance between the samples and the hyperplane, and the classification and recognition results of EEG features were obtained. The frontal channel TBR change values of each subject student in virtual reality technology art history teaching were significantly lower than those of the traditional art history teaching mode (p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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