Paper
10 October 2023 Research on deep learning-based facial expression recognition and its application in online learning state monitoring
Qisheng Wang, Xiaofei Yan, Yanqiu Wang
Author Affiliations +
Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127991Z (2023) https://doi.org/10.1117/12.3005824
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia
Abstract
This paper aims to research and develop a facial expression recognition algorithm based on convolutional neural networks (CNN) and apply it to a real-time facial expression recognition system. Firstly, we introduce the Local Binary Pattern (LBP) and CNN as commonly used facial recognition algorithms, discussing their characteristics and application areas. We then describe the experimental process in detail, conducting emotion recognition experiments using the FER2013 dataset and performing data preprocessing and augmentation steps. We design a CNN-based model architecture and set the parameters of the model. In the results and analysis section, we compare the performance of our model with other baseline models and discuss possible directions for improvement. Finally, we conclude that our algorithm achieves high accuracy in the experiments and provide prospects for future research and applications.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Qisheng Wang, Xiaofei Yan, and Yanqiu Wang "Research on deep learning-based facial expression recognition and its application in online learning state monitoring", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127991Z (10 October 2023); https://doi.org/10.1117/12.3005824
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KEYWORDS
Facial recognition systems

Emotion

Machine learning

Deep learning

Feature extraction

Online learning

Detection and tracking algorithms

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