Abstract
In order to improve the accuracy of feature extraction of students’ Ideological and political learning behavior, a method of feature extraction of students’ Ideological and political learning behavior based on convolutional neural network is proposed. The image of students’ Ideological and political learning behavior is obtained and stored, and the stored image is corrected. On the basis of image correction, the similarity measurement of students’ image spatial structure information details and the representation of image spatial structure information details are used to extract the characteristics of students’ Ideological and political learning behavior based on convolutional neural network. The experimental results show that the method based on convolution neural network not only improves the accuracy of feature extraction, but also reduces the time of feature extraction.
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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Jiang, Hb. (2021). Feature Extraction Method of Students’ Ideological and Political Learning Behavior Based on Convolutional Neural Network. In: Fu, W., Liu, S., Dai, J. (eds) e-Learning, e-Education, and Online Training. eLEOT 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 390. Springer, Cham. https://doi.org/10.1007/978-3-030-84386-1_42
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DOI: https://doi.org/10.1007/978-3-030-84386-1_42
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