A NOVEL NETWORK MODEL BASED ICA FILTER FOR FACE RECOGNITION

被引：0
|
作者：
Zhang, Yongqing [1 ,2 ]
Geng, Tianyu [3 ]
Cai, Ying [4 ]
机构：
[1] Chengdu Univ Informat Technol, Sch Comp Sci, Chengdu 610225, Sichuan, Peoples R China
[2] Univ Elect Sci & Technol China, Sch Comp Sci & Engn, Chengdu 611731, Sichuan, Peoples R China
[3] Sichuan Univ, Sch Comp Sci, Chengdu 610065, Sichuan, Peoples R China
[4] Sichuan Agr Univ, Coll Informat Engn, Yaan 625014, Peoples R China
来源：
2017 14TH INTERNATIONAL COMPUTER CONFERENCE ON WAVELET ACTIVE MEDIA TECHNOLOGY AND INFORMATION PROCESSING (ICCWAMTIP) | 2017年
基金：
中国国家自然科学基金;
关键词：
Face Recognition; ICANet; Feret; Convolution Network;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Despite the great success of deep learning convolution networks, researchers are not yet clear about its feature learning mechanism and optimal network configuration. In this paper, we present a cascaded linear convolution network based on ICA filters, termed ICANet. ICANet mainly includes three parts: convolution layer, binary hash and block histogram. The results show that ICANet has a very good performance in face recognition tasks.
引用
收藏
页码：120 / 123
页数：4
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