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Facial emotion recognition using an ensemble of multi-level convolutional neural networks
Citation
Nguyen, HD and Yeom, S and Lee, G-S and Yang, H-J and Na, I-S and Kim, S-H, Facial emotion recognition using an ensemble of multi-level convolutional neural networks, International Journal of Pattern Recognition and Artificial Intelligence, 33, (11) pp. 1940015. ISSN 0218-0014 (2019) [Refereed Article]
Copyright Statement
Copyright 2019 World Scientific Publishing Company
DOI: doi:10.1142/S0218001419400159
Abstract
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.
Item Details
Item Type: | Refereed Article |
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Keywords: | ensemble model, facial emotion recognition in the wild, multi-level convolutional neural networks |
Research Division: | Information and Computing Sciences |
Research Group: | Computer vision and multimedia computation |
Research Field: | Pattern recognition |
Objective Division: | Information and Communication Services |
Objective Group: | Information systems, technologies and services |
Objective Field: | Information systems, technologies and services not elsewhere classified |
UTAS Author: | Yeom, S (Dr Soonja Yeom) |
ID Code: | 132151 |
Year Published: | 2019 |
Web of Science® Times Cited: | 2 |
Deposited By: | Information and Communication Technology |
Deposited On: | 2019-04-24 |
Last Modified: | 2020-05-18 |
Downloads: | 0 |
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