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Multimodal Emotion Detection for Education and Work Environment by Using Improved Artificial Intelligence Machine Vision System Cover

Multimodal Emotion Detection for Education and Work Environment by Using Improved Artificial Intelligence Machine Vision System

Journal of Automation, Mobile Robotics and Intelligent Systems
Volume 20 (2026): Issue 2 (June 2026)
By: ,  ,  ,   and    
Open Access
|Jun 2026
Figures & tables

Figures & Tables

Figure 1.

Flow process of training and testing the face emotion detection AI model using machine learning methods

Figure 2.

Block diagram of training and testing the ECG emotion detection AI model with machine learning methods

Figure 3.

Overall flowchart of facial emotion AI model training process

Figure 4.

Overall flowchart of facial emotion AI model testing process

Figure 5.

Overall flowchart of ECG emotion AI model training process

Figure 6.

Overall flowchart of ECG emotion AI model testing process

Figure 7.

Accuracy of training and validation of facial emotion AI model

Figure 8.

Loss of training and validation of facial emotion AI model

Figure 9.

Accuracy of training and validation of facial emotion AI model

Figure 10.

Accuracy of training and validation of facial emotion AI model

Figure 11.

Accuracy of training and validation of facial emotion AI model

Figure 12.

Classification report using random forest

Figure 13.

Display combining emotion and advice in the web browser

Results of experiment_

EmotionProbability (%)
Happy98.63
Neutral56.60
Sad39.58
Surprise77.86
Fear26.36
Angry41.34
Digust27.19
DOI: https://doi.org/10.14313/jamris-2026-019 | Journal eISSN: 2080-2145 | Journal ISSN: 1897-8649
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Language: English
Page range: 53 - 62
Submitted on: Jul 1, 2024
Accepted on: Sep 6, 2024
Published on: Jun 22, 2026
Published by: Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Artificial Intelligence,
Multimodal Emotion Detection,
Machine Learning,
Convolutional Neural Network,
Machine Vision System
Related subjects:
Computer sciences,
Artificial intelligence,
Engineering,
Electrical engineering,
Control engineering, metrology and testing,
Mechanical engineering,
Fundamentals of mechanical engineering

© 2026 Wan Mohd Bukhari Wan Daud, Adnan Kiral, Mohamed Osman Tokhi, Lee Chung Yee, Muhammad Muzhafar Mohammad Zawawi, published by Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 20 (2026): Issue 2 (June 2026)
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