Deep learning methods for facial expression recognition
Deep learning is very popular methods for facial expression recognition (FER) and classification. Different types of deep learning algorithms have been used for FER such as deep belief network (DBN) and convolutional neural network (CNN). In this paper, we analyze various deep learning methods...
| Main Authors: | , |
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| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2019
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/79711/ http://irep.iium.edu.my/79711/1/79711_Deep%20Learning%20Methods%20for%20Facial%20_conf.%20article.pdf http://irep.iium.edu.my/79711/2/79711_Deep%20Learning%20Methods%20for%20Facial%20_scopus.pdf |
| Summary: | Deep learning is very popular methods for facial
expression recognition (FER) and classification. Different types
of deep learning algorithms have been used for FER such as
deep belief network (DBN) and convolutional neural network
(CNN). In this paper, we analyze various deep learning methods
and their results. We have chosen Deep convolutional neural
network as the best algorithms for facial expression detection
and classification. In our study, we have tested the algorithm
using Japanese Female facial expressions database (JAFFE)
datasets by anaconda software. The deep convolution neural
networks with JAFFE datasets accuracy rate around 97.01%. |
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