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Using Facial Expression to Detect Emotion in E-learning System: A Deep Learning Method

机译:使用面部表情检测电子学习系统中的情绪:一种深度学习方法

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E-learning system is becoming more and more popular among students nowadays. However, the emotion of students is usually neglected in e-learning system. This study is mainly concerned about using facial expression to detect emotion in e-learning system. A deep learning method called convo-lutional neural network (CNN) is used in our research. Firstly, CNN is introduced to detect emotion in e-learning system based on using facial expression in this paper. Secondly, the training process and testing process of CNN are described. To learn about the accuracy of CNN in emotion detection, three databases (CK+, JAFFE and NVIE) are chosen to train and test the model. 10-fold cross validation method is used to calculate the accuracy. Thirdly, we introduce how to apply the trained CNN to e-learning system, and the design of e-learning system with emotion detection module is given. At last, we propose the design of an experiment to evaluate the performance of this method in real e-learning system.
机译:如今,电子学习系统在学生中越来越受欢迎。然而,在电子学习系统中,学生的情感通常被忽略。这项研究主要涉及在电子学习系统中使用面部表情来检测情绪。我们的研究中使用了一种称为卷积神经网络(CNN)的深度学习方法。本文首先介绍了基于面部表情的CNN,用于在电子学习系统中检测情感。其次,描述了CNN的训练过程和测试过程。为了了解CNN在情感检测中的准确性,我们选择了三个数据库(CK +,JAFFE和NVIE)来训练和测试该模型。 10倍交叉验证方法用于计算准确性。第三,介绍了如何将训练有素的CNN应用于电子学习系统,并给出了带有情感检测模块的电子学习系统的设计。最后,我们提出了一个实验设计,以评估该方法在实际电子学习系统中的性能。

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