Facial emotion recognition using an ensemble of multi-level convolutional neural networks
journal contribution
posted on 2023-05-20, 03:00 authored by Nguyen, HD, Soonja YeomSoonja Yeom, Lee, G-S, Yang, H-J, Na, I-S, Kim, S-HEmotion recognition plays an indispensable role in human-machine interaction system. The process includes finding interesting facial regions in images and classifying them into one of seven classes: angry, disgust, fear, happy, neutral, sad, and surprise. Although many breakthroughs have been made in image classification, especially in facial expression recognition, this research area is still challenging in terms of wild sampling environment. In this paper, we used multi-level features in a convolutional neural network for facial expression recognition. Based on our observations, we introduced various network connections to improve the classification task. By combining the proposed network connections, our method achieved competitive results compared to state-of-the-art methods on the FER2013 dataset.
History
Publication title
International Journal of Pattern Recognition and Artificial IntelligenceVolume
33Issue
11Pagination
1940015ISSN
0218-0014Department/School
School of Information and Communication TechnologyPublisher
World Scientific Publ Co Pte LtdPlace of publication
Journal Dept Po Box 128 Farrer Road, Singapore, Singapore, 912805Rights statement
Copyright 2019 World Scientific Publishing CompanyRepository Status
- Restricted