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

页码：142 / 145

页数：4

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