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Facial emotion recognition using an ensemble of multi-level convolutional neural networks

Nguyen, HD, Yeom, S ORCID: 0000-0002-5843-101X, Lee, G-S, Yang, H-J, Na, I-S and Kim, S-H 2019 , 'Facial emotion recognition using an ensemble of multi-level convolutional neural networks' , International Journal of Pattern Recognition and Artificial Intelligence , pp. 1-17 , doi: 10.1142/S0218001419400159.

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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 Type: Article
Authors/Creators:Nguyen, HD and Yeom, S and Lee, G-S and Yang, H-J and Na, I-S and Kim, S-H
Keywords: ensemble model, facial emotion recognition in the wild, multi-level convolutional neural networks
Journal or Publication Title: International Journal of Pattern Recognition and Artificial Intelligence
Publisher: World Scientific Publ Co Pte Ltd
ISSN: 0218-0014
DOI / ID Number: 10.1142/S0218001419400159
Copyright Information:

Copyright 2019 World Scientific Publishing Company

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