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01-Applied Mathematics & Information Sciences
An International Journal
               
 
 
 
 
 
 
 
 
 
 
 

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Volumes > Volume 13 > No. 5

 
   

Improved Facial Expression Recognition with Xception Deep Net and Preprocessed Images

PP: 859-865
Author(s)
Maksat Kanatov, Lyazzat Atymtayeva, Mateus Mendes,
Abstract
Automated Facial Expression Recognition (FER) is an important part of computer-human interaction. For decades, researchers and scientists have been trying to create a model of artificial intelligence that could think, learn, make decisions and act in a way similar to a real person. Among other skills, such model needs to recognise human facial expression to understand non-verbal language. The present paper describes a method to fine tune the FER process in images, using deep learning CNN model Xception, with preprocessing the images. The method has shown improved results when applied to different datasets.

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