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Improving Performance of Facial Expression Recognition using Multi-task Learning of Neural Networks

Published:21 October 2015Publication History

ABSTRACT

Facial expression recognition is an important topic in the field of human-agent interaction, because facial expression is simple and impressive signal which human can send to others. Though there have been numerous studies on facial image analysis, the performance of expression recognition is still not acceptable due to the diversity of human expression and enormous variations in facial images. In this paper, we try to improve the performance of facial expression recognition by using multi-task learning techniques of neural networks. Through computational experiments on a benchmark database, we show positive possibility of performance improvement using multi-task learning.

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  1. Improving Performance of Facial Expression Recognition using Multi-task Learning of Neural Networks

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        cover image ACM Other conferences
        HAI '15: Proceedings of the 3rd International Conference on Human-Agent Interaction
        October 2015
        254 pages
        ISBN:9781450335270
        DOI:10.1145/2814940

        Copyright © 2015 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 21 October 2015

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