(An) analog-digital hybrid CNN face recognition processor for always-on mobile devices실시간 모바일 기기를 위한 아날로그-디지털 혼성 CNN 얼굴 인식 프로세서

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An ultra-low power analog-digital hybrid always-on face recognition (FR) processor integrated with a CMOS image sensor (CIS) is proposed for the wearable mobile devices applications such as user authentication. The proposed processor is the first IC with full process of FR in a single chip. The processor adopts analog-digital hybrid convolution operation for efficient integration of CNN processor with CIS. The analog convolution processor is proposed for the computation of the $1^st$ layer of CNN and the quantization operation without an ADC that can achieve 15.7% power reduction with 1.37% minimal accuracy loss. In addition, the analog weighted-sum unit with low power ($< 20\muW$) and high efficiency (> 5.18TOPS/W) is proposed with switched-drain regulation (SDR) current mirror which can achieve less than 6% mirroring error. The processor is simulated in 65-nm CMOS technology, $15.84mm^2$ area with 2.5V and 1.2V for analog domain and 0.77-1.1V for digital domain. It consumes 0.141mW to evaluate one face at 1 fps and achieves 96.18% FR accuracy in LFW dataset.
Advisors
Yoo, Hoi-Junresearcher유회준researcher
Description
한국과학기술원 :전기및전자공학부,
Publisher
한국과학기술원
Issue Date
2019
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2019.8,[iii, 28 p :]

Keywords

Always-on▼aanalog-digital hybrid▼aCNN▼aCMOS image sensor▼aface detection▼aface recognition; 실시간▼a아날로그-디지털 혼성▼aCNN▼aCMOS 이미지 센서▼a얼굴 탐지▼a얼굴 인식

URI
http://hdl.handle.net/10203/283035
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=875329&flag=dissertation
Appears in Collection
EE-Theses_Master(석사논문)
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