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Facial Emotion Recognition in Children Using Convolutional Neural Network with Data Augmentation

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2025, 30(2), pp.21-31
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : January 3, 2025
  • Accepted : January 24, 2025
  • Published : February 28, 2025

Hyora Lee 1 Beom Kwon 1

1동덕여자대학교

Accredited

ABSTRACT

In this study, we investigate how to recognize children's emotions from their face images. Children's face image datasets are fewer in number than adult face image datasets and are often not publicly available on the Internet due to child research ethics. In this study, we propose a new data augmentation technique to improve the emotion recognition accuracy of the convolutional neural network (CNN) model in a situation where the number of samples in the child face image dataset is limited. To demonstrate the effectiveness of the proposed data augmentation technique, we conducted experiments using the child face image dataset of the National Institute of Mental Health, which is publicly available on the Internet. The experimental results showed that the CNN model achieved the best performance in the emotion recognition task when the proposed data augmentation technique was applied.

Citation status

* References for papers published after 2023 are currently being built.

This paper was written with support from the National Research Foundation of Korea.