Student Attention Base Facial Emotion State Recognition Using Convolutional Neural Network
Lecture Notes in Networks and Systems
; 551:579-589, 2023.
Article
in English
| Scopus | ID: covidwho-2296254
ABSTRACT
E-learning system advancements give students new opportunities to better their academic performance and access e-learning education. Because it provides benefits over traditional learning, e-learning is becoming more popular. The coronavirus disease pandemic situation has caused educational institution cancelations all across the world. Around all over the world, more than a billion students are not attending educational institutions. As a result, learning criteria have taken on significant growth in e-learning, such as online and digital platform-based instruction. This study focuses on this issue and provides learners with a facial emotion recognition model. The CNN model is trained to assess images and detect facial expressions. This research is working on an approach that can see real-time facial emotions by demonstrating students' expressions. The phases of our technique are face detection using Haar cascades and emotion identification using CNN with classification on the FER 2013 datasets with seven different emotions. This research is showing real-time facial expression recognition and help teachers adapt their presentations to their student's emotional state. As a result, this research detects that emotions' mood achieves 62% accuracy, higher than the state-of-the-art accuracy while requiring less processing. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Convolutional neural networks (CNN); E-learning; Facial expression; Intelligent education management system; Classification (of information); Convolution; Convolutional neural networks; Education computing; Emotion Recognition; Face recognition; Learning systems; Speech recognition; Convolutional neural network; E - learning; Education management; Educational institutions; Facial emotions; Facial Expressions; Intelligent educations; Management systems; Students
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
Lecture Notes in Networks and Systems
Year:
2023
Document Type:
Article
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