Facial Emotion Recognition of Students using Convolutional Neural Network

Imane Lasri · Anouar Riad Solh · Mourad Elbelkacemi

126 citations0/0 files storedInternational Conference on Intelligent Computing in Data Sciences (ICDS)

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Emotion and Mood Recognition Face recognition and analysis Face and Expression Recognition

Abstract

Nowadays, deep learning techniques know a big success in various fields including computer vision. Indeed, a convolutional neural networks (CNN) model can be trained to analyze images and identify face emotion. In this paper, we create a system that recognizes students' emotions from their faces. Our system consists of three phases: face detection using Haar Cascades, normalization and emotion recognition using CNN on FER 2013 database with seven types of expressions. Obtained results show that face emotion recognition is feasible in education, consequently, it can help teachers to modify their presentation according to the students' emotions.

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References

1997A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting 1971Constants across cultures in the face and emotion.2014The Faces of Engagement: Automatic Recognition of Student Engagementfrom Facial Expressions 1978Nonverbal Communication: The State of the Art 2018An Emotion Recognition Model Based on Facial Recognition in Virtual Learning Environment 2015Automatic Detection of Learning-Centered Affective States in the Wild 2016Student Emotion Recognition System (SERS) for e-learning Improvement Based on Learner Concentration Metric

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2022Facial emotion recognition of deaf and hard-of-hearing students for engagement detection using deep learning 2022A Novel Approach for Emotion Recognition Based on EEG Signal Using Deep Learning 2024Facial Emotion Recognition (FER) using Convolutional Neural Network (CNN)

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