深度学习在数学教育中的应用

Yuyang Sun, Qingzhong Li
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引用次数: 4

摘要

本文提出了一种基于卷积神经网络的面部表情识别新方法,设计了一种新的卷积神经网络并扩展了表情库。在CK+和JAFFE数据库的基础上,增加200个困倦表达和聚焦表达。困倦表情和专注表情是学生学习过程中最常见的表情,认识到困倦表情和专注表情可以帮助教师了解学生的学习情况,改变教学重点。实验结果表明,与传统的面部表情识别方法相比,该网络具有更高的准确率和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Application of Deep Learning in Mathematical Education
A novel method of facial expression recognition based on convolutional neural network is proposed in this paper, we design a new convolutional neural network and expand the expression database. On the basis of CK+ and JAFFE databases, adding 200 sleepy expressions and focused expressions. The sleepy expression and the focus expression is the most common expression in the students’ learning process, recognizing that can help teacher know the students’ learning situation and change the point of teaching. In comparison to the traditional method of facial expression, the experimental results show that the proposed network is more accurate and efficient.
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