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Facial Expression Recognition via Broad Learning System
Zhang,Tong1; Liu,Zhulin2; Wang,Xue Han1; Xing,Xiao Fen1; Chen,C. L.Philip1; Chen,Enhong1
2019-01-16
Source PublicationProceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
Pages1898-1902
AbstractIn recent years, research on facial expression Recognition (FER) has become an increasingly active research topic. Deep learning is a new area, which gives a new way to classify images of human faces into emotion categories. However, it faces many difficulties caused by poor robustness and real-time performance. This paper designs a new architecture network based on Broad Learning System (BLS) for facial expressions Recognition. It is established as a flat network. The original inputs are transferred and placed as mapped features in feature nodes, while the structure is expanded in wide sense in the enhancement nodes. To evaluate our architecture we tested the proposed method with the Extended Cohn-Kanade Dataset (CK+). The experimental results show that the BLS approach is very effective in facial expression Recognition to compare with convolutional neural networks.
Keywordbroad learning system emotion Recognition Facial expression Recognition feature learning
DOI10.1109/SMC.2018.00328
URLView the original
Language英语
Scopus ID2-s2.0-85062212026
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Cited Times [WOS]:3   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Sch. of Electronics and Information,South China University of Technology,Guangzhou,China
2.Dept. of Computer and Inform. Science,University of Macau,Macao
Recommended Citation
GB/T 7714
Zhang,Tong,Liu,Zhulin,Wang,Xue Han,et al. Facial Expression Recognition via Broad Learning System[C],2019:1898-1902.
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