Weighted-fusion feature of MB-LBPUH and HOG for facial expression recognition-Reference-Cited by-同舟云学术

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Weighted-fusion feature of MB-LBPUH and HOG for facial expression recognition

Published:2019-10-29 Issue:8 Volume:24 Page:5859-5875
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Wang Yan,Li Ming,Zhang Congxuan,Chen Hao,Lu Yuming

Funder

National Natural Science Foundation of China

Key Research and Development Program of Jiangxi Province

Advantage Subject Team Project of Jiangxi Province

Science Technique Project of Jiangxi Province

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00500-019-04380-x.pdf

Reference70 articles.

1. Abdulrahman M, Gwadabe TR, Abdu FJ, Eleyan A (2014) Gabor wavelet transform based facial expression recognition using PCA and LBP. In: Proceedings of IEEE conference on signal processing and communications applications, pp 2265–2268

2. Alsmirat MA, Al-Alem F, Al-Ayyoub M, Jararweh Y, Gupta B (2019) Impact of digital fingerprint image quality on the fingerprint recognition accuracy. Multimed Tools Appl 78:3649–3688

3. Bacivarov I, Corcoran PM (2009) Facial expression modeling using component AAM models—gaming applications. In: Proceedings of IEEE conference on consumer electronics society’s games innovations, pp 1–16

4. Benitez-Garcia G, Nakamura T, Kaneko M (2017) Facial expression recognition based on local fourier coefficients and facial fourier descriptors. J Signal Inform Process 8:132–151

5. Chen Y-S (2019) Performance identification in large-scale class data from advanced facets of computational intelligence and soft computing techniques. Int J High Perform Comput Netw 13(3):283–293

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