Title
Improving Performance of Facial Expression Recognition using Multi-task Learning of Neural Networks
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.
Year
DOI
Venue
2015
10.1145/2814940.2815011
HAI
DocType
Citations 
PageRank 
Conference
1
0.37
References 
Authors
4
3
Name
Order
Citations
PageRank
Jeongin Seo1132.35
Changhun Hyun210.37
Hyeyoung Park319432.70