Face Recognition Research Based on Fully Convolution Neural Network

被引：0
|
作者：
YangWang [1 ]
Zheng, Jiachun [1 ]
机构：
[1] Jimei Univ, Informat Engn Coll, Xiamen 361021, Peoples R China
来源：
2017 2ND INTERNATIONAL CONFERENCE ON MECHATRONICS AND INFORMATION TECHNOLOGY (ICMIT 2017) | 2017年
关键词：
Face recognition; Caffe; CNN; feature extraction;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Face recognition technology has always been a hot topic, and has a widely application in our daily life. In recent years, with the rapid development of deep learning and the birth of various frameworks, face recognition is provided a new platform and ushered in a new opportunity. In this paper, a fully Convolution Neural Network(CNN) based on the Caffe framework and GPU is put forward for face recognition. The accuracy rate of it reaches 99% in the test set. Compared with the traditional extraction feature combined with the classifier method, CNN has a unique advantage, and doesn't need to manually extract features.
引用
收藏
页码：142 / 145
页数：4
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