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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-H
Emotion 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 Intelligence

Volume

33

Issue

11

Pagination

1940015

ISSN

0218-0014

Department/School

School of Information and Communication Technology

Publisher

World Scientific Publ Co Pte Ltd

Place of publication

Journal Dept Po Box 128 Farrer Road, Singapore, Singapore, 912805

Rights statement

Copyright 2019 World Scientific Publishing Company

Repository Status

  • Restricted

Socio-economic Objectives

Information systems, technologies and services not elsewhere classified

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