Deep Learning Method of Facial Expression Recognition Based on Gabor Filter Bank Combined with PCNN-Reference-Cited by-同舟云学术

Deep Learning Method of Facial Expression Recognition Based on Gabor Filter Bank Combined with PCNN

Published:2023-04-24 Issue:2 Volume:131 Page:955-971
ISSN:0929-6212
Container-title:Wireless Personal Communications
language:en
Short-container-title:Wireless Pers Commun

Author:

Yao Lisha^ORCID,Zhao Haifeng

Funder

Key Laboratory of Microbial Resources and Drug Development in Guizhou Province

Key Laboratory of Engineering Structures Damage and Diagnosis of Hunan Province

Data to Decisions Cooperative Research Centres

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications

Link

https://link.springer.com/content/pdf/10.1007/s11277-023-10463-8.pdf

Reference32 articles.

1. Liu, Q. M., & Xin, Y. Y. (2020). Face expression recognition based on end-to-end low-quality face images. Journal of Chinese Computer Systems, 041(003), 668–672.

2. Li, T. T., Hu, Y. L., & Wei, F. L. (2020). Improved facial expression recognition algorithm based on GAN and application. Journal of Jilin University (Science Edition), 058(003), 605–610.

3. Qiang, W., Zhou, X. Y., Xu, H. N., Li, D. P., & An, H. R. (2020). Micro-expression recognition based on LBP and two-stream spatial-temporal neural network. Information and Contro, 49(06), 37–43.

4. Wu, H., Hu, M., Gao, Y., Wang, X. H., & Huang, Z. (2020). Facial expression recognition based on DCLBP and HOAG. Journal of Electronic Measurement and Instrumentation, 2, 73–79.

5. Zhou, H. L., Kinman, L., & He, X. J. (2016). Shape-appearance-correlated active appearance model. Pattern Recognition, 56(1), 88–99.

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