Low-Power Convolutional Neural Network Processor for a Face-Recognition System

被引：24

作者：

Bong, Kyeongryeol ^{[1
]}

Choi, Sungpill ^{[1
]}

Kim, Changhyeon ^{[1
]}

Yoo, Hoi-Jun ^{[2
]}

机构：

[1] Korea Adv Inst Sci & Technol, Daejeon, South Korea

[2] Korea Adv Inst Sci & Technol, Dept Elect Engn, Daejeon, South Korea

来源：

IEEE MICRO | 2017年 / 37卷 / 06期

关键词：

application-based system; authentication; face recognition; image processing and computer vision; low-power design; neural nets; special-purpose system;

D O I：

10.1109/MM.2017.4241350

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The authors propose a low-power convolutional neural network (CNN)-based face recognition system for user authentication in smart devices. The system comprises an always-on functional CMOS image sensor (CIS) for imaging and face detection, and a low-power CNN processor (CNNP) for face verification. Implemented in 65-nm CMOS technology, the system consumes 0.62 mW to evaluate one face at 1 fps and achieves 97 percent accuracy.

引用

页码：30 / 38

页数：9

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