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Prediction of Rolling Force Based on a Fusion of Extreme Learning Machine and Self Learning Model of Rolling Force Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Facial Expression Recognition Based on Deep Learning: A Survey

Author : Ting Zhang

Published in: Advances in Intelligent Systems and Interactive Applications

Publisher: Springer International Publishing

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Abstract

Facial expression recognition (FER) enables computers to understand human emotions and is the basis and prerequisite for quantitative analysis of human emotions. As a challenging interdisciplinary in biometrics and emotional computing, FER has become a research hotspot in the field of pattern recognition, computer vision and artificial intelligence both at home and abroad. As a new machine learning theory, deep learning not only emphasizes the depth of learning model, but also highlights the importance of feature learning for network model, and has made some research achievements in facial expression recognition. In this paper, the current research states are analyzed mostly from the latest facial expression extraction algorithm and the FER algorithm based on deep learning a comparison is made of these methods. Finally, the research challenges are generally concluded, and the possible trends are outlined.

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Metadata
Title
Facial Expression Recognition Based on Deep Learning: A Survey
Author
Ting Zhang
Copyright Year
2018
Book
Advances in Intelligent Systems and Interactive Applications

Print ISBN: 978-3-319-69095-7

Electronic ISBN: 978-3-319-69096-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-69096-4_48

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