中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
A hybrid-supervision learning algorithm for real-time un-completed face recognition

文献类型:期刊论文

作者Zhao, Shuhuan1,2; Liu, Wen1,2; Liu, Shuaiqi1,2,3; Ge, Jiaqi1,2; Liang, Xiaolin1,2
刊名COMPUTERS & ELECTRICAL ENGINEERING
出版日期2022-07-01
卷号101页码:17
关键词Face recognition Feature fusion Hybrid supervised learning Multiple marginal Fisher analysis
ISSN号0045-7906
DOI10.1016/j.compeleceng.2022.108090
通讯作者Liu, Shuaiqi(shdkj_l918@163.com)
英文摘要It is still an important and challenging problem for face recognition with occlusion, small sample size, various expressions, and poses, called un-completed face recognition. So we design a simple but effective hybrid-supervision learning frame by fusing the advantages of supervised and unsupervised features. In the supervised branch, we propose an effective feature learning method: HMMFA. In the unsupervised branch, we improve the PCANet to extract more effective local information. In the fusion stage, we further extract the discriminant features contained in the hybrid features and then take SVM as the final classifier. Because the proposed method requires no auxiliary set and has less parameter number than that of deep learning methods, it has a low storage requirement, which makes it more economical and practical for small communities. Experiments on four databases show the effectiveness and efficiency of our method.
WOS关键词REGRESSION
资助项目National Natural Science Foundation of China[62172139] ; Natural Science Foundation of Hebei Province[F2020201025] ; Natural Science Foundation of Hebei Province[F2019201151] ; Natural Science Foundation of Hebei Province[F2019201362] ; Natural Science Foundation of Hebei Province[F2018210148] ; Science Research Project of Hebei Province[BJ2020030] ; Science Research Project of Hebei Province[QN2017306] ; Open Project Program of NLPR[202200007] ; Foundation of President of Hebei University[XZJJ201909] ; High-Performance Computing Center of Hebei University
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000849743000011
出版者PERGAMON-ELSEVIER SCIENCE LTD
资助机构National Natural Science Foundation of China ; Natural Science Foundation of Hebei Province ; Science Research Project of Hebei Province ; Open Project Program of NLPR ; Foundation of President of Hebei University ; High-Performance Computing Center of Hebei University
源URL[http://ir.ia.ac.cn/handle/173211/50023]  
专题自动化研究所_模式识别国家重点实验室_视频内容安全团队
通讯作者Liu, Shuaiqi
作者单位1.Machine Vis Technol Innovat Ctr Hebei, Baoding 071002, Peoples R China
2.Hebei Univ, Coll Elect & Informat Engn, Baoding 071002, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit NLPR, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Zhao, Shuhuan,Liu, Wen,Liu, Shuaiqi,et al. A hybrid-supervision learning algorithm for real-time un-completed face recognition[J]. COMPUTERS & ELECTRICAL ENGINEERING,2022,101:17.
APA Zhao, Shuhuan,Liu, Wen,Liu, Shuaiqi,Ge, Jiaqi,&Liang, Xiaolin.(2022).A hybrid-supervision learning algorithm for real-time un-completed face recognition.COMPUTERS & ELECTRICAL ENGINEERING,101,17.
MLA Zhao, Shuhuan,et al."A hybrid-supervision learning algorithm for real-time un-completed face recognition".COMPUTERS & ELECTRICAL ENGINEERING 101(2022):17.

入库方式: OAI收割

来源:自动化研究所

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