@article{M08A3E646,
title = "Effect Analysis of Data Imbalance for Emotion Recognition
Based on Deep Learning",
journal = "KIPS Transactions on Computer and Communication Systems",
year = "2023",
issn = "2287-5891",
doi = "10.3745/KTCCS.2023.12.8.235",
author = "Hajin Noh/Yujin Lim",
keywords = "Biased Data, XAI, LIME, Emotional Recognition, CNN",
abstract = "In recent years, as online counseling for infants and adolescents has increased, CNN-based deep learning models are widely used
as assistance tools for emotion recognition. However, since most emotion recognition models are trained on mainly adult data, there
are performance restrictions to apply the model to infants and adolescents. In this paper, in order to analyze the performance constraints,
the characteristics of facial expressions for emotional recognition of infants and adolescents compared to adults are analyzed through
LIME method, one of the XAI techniques. In addition, the experiments are performed on the male and female groups to analyze the
characteristics of gender-specific facial expressions. As a result, we describe age-specific and gender-specific experimental results based
on the data distribution of the pre-training dataset of CNN models and highlight the importance of balanced learning data."
}