Finger Vein Recognition Based on Deep Learning

被引：0
|
作者：
Liu, Wenjie [1 ,2 ,3 ]
Li, Weijun [1 ,2 ,3 ]
Sun, Linjun [1 ,2 ,3 ]
Zhang, Liping [1 ,2 ,3 ]
Chen, Peng [1 ,2 ,3 ]
机构：
[1] Chinese Acad Sci, Inst Semicond, Beijing 100083, Peoples R China
[2] Cognit Comp Technol Wei Fu Joint Lab, Beijing 100083, Peoples R China
[3] Univ Chinese Acad Sci, Sch Microelect, Beijing 100029, Peoples R China
来源：
PROCEEDINGS OF THE 2017 12TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA) | 2017年
关键词：
biometrics; finger vein recognition; deep learning; convolutional neural network; traditional algorithm; EXTRACTION;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
As a new biometric technology, finger vein recognition has received much attention in recent years. Since deep learning is an end-to-end system, and has achieved very good results in such fields as face recognition and target detection, we try to apply it to finger vein recognition. In this paper, we adopt seven layers of CNN which include 5 convolution layers and 2 fully-connected layers. This network obtains a recognition rate of 99.53%, which proves to be better performing than traditional algorithm.
引用
收藏
页码：205 / 210
页数：6
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