Low-Power Convolutional Neural Network Processor for a Face-Recognition System
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Bong, Kyeongryeol | ko |
| dc.contributor.author | Choi, Sungpill | ko |
| dc.contributor.author | Kim, Changhyeon | ko |
| dc.contributor.author | Yoo, Hoi-Jun | ko |
| dc.date.accessioned | 2018-02-21T05:54:27Z | - |
| dc.date.available | 2018-02-21T05:54:27Z | - |
| dc.date.created | 2018-02-05 | - |
| dc.date.created | 2018-02-05 | - |
| dc.date.created | 2018-02-05 | - |
| dc.date.issued | 2017-11 | - |
| dc.identifier.citation | IEEE MICRO, v.37, no.6, pp.30 - 38 | - |
| dc.identifier.issn | 0272-1732 | - |
| dc.identifier.uri | http://hdl.handle.net/10203/240171 | - |
| dc.description.abstract | 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. | - |
| dc.language | English | - |
| dc.publisher | IEEE COMPUTER SOC | - |
| dc.title | Low-Power Convolutional Neural Network Processor for a Face-Recognition System | - |
| dc.type | Article | - |
| dc.identifier.wosid | 000422855000006 | - |
| dc.identifier.scopusid | 2-s2.0-85038106848 | - |
| dc.type.rims | ART | - |
| dc.citation.volume | 37 | - |
| dc.citation.issue | 6 | - |
| dc.citation.beginningpage | 30 | - |
| dc.citation.endingpage | 38 | - |
| dc.citation.publicationname | IEEE MICRO | - |
| dc.contributor.localauthor | Yoo, Hoi-Jun | - |
| dc.description.isOpenAccess | N | - |
| dc.type.journalArticle | Article | - |
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