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Paper Abstract and Keywords
Presentation 2026-03-27 09:55
A 0.8μm 32Mpixel Always-On CMOS Image Sensor with Windmill-Pattern Edge Extraction and On-Chip DNN
Mamoru Sato, Sachio Akebono, Kazuyoshi Yasuoka, Eriko Kato, Masahiro Tsuruta, Kensuke Ota, Kazuki Haraguchi, Masahiro Watanabe, Genki Fujii, Koichiro Yamanaka, Kazunori Yasuda, Satoshi Minami, Katsuhiko Hanzawa, Kohei Matsuda, Akihiko Kato, Yosuke Ueno (SSS)
Abstract (in Japanese) (See Japanese page) 
(in English) This paper presents a CMOS image sensor (CIS) that integrates two operation modes: a high-resolution viewing mode with 0.8 μm 32 Mpixels and a low-power always-on object recognition mode consuming 2.67 mW at 10 fps. The CIS features a unique windmill-pattern analog edge extraction circuit that is resilient to illumination variations. An on-chip deep neural network processor was implemented alongside a compact algorithm with only 12 KB for coefficients and 48 KB for working memory. The design incorporates separate circuit areas for high-speed viewing and low-power sensing modes, thereby ensuring optimal performance and energy efficiency.
Keyword (in Japanese) (See Japanese page) 
(in English) always-on / artificial intelligence / deep neural network / edge extraction / ratio-to-digital converter / / /  
Reference Info. ITE Tech. Rep., vol. 50, no. 14, IST2026-14, pp. 18-22, March 2026.
Paper # IST2026-14 
Date of Issue 2026-03-20 (IST) 
ISSN Online edition: ISSN 2424-1970
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Conference Information
Committee IST  
Conference Date 2026-03-27 - 2026-03-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Kikai-Shinko-Kaikan Bldg. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IST 
Conference Code 2026-03-IST 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A 0.8μm 32Mpixel Always-On CMOS Image Sensor with Windmill-Pattern Edge Extraction and On-Chip DNN 
Sub Title (in English)  
Keyword(1) always-on  
Keyword(2) artificial intelligence  
Keyword(3) deep neural network  
Keyword(4) edge extraction  
Keyword(5) ratio-to-digital converter  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Mamoru Sato  
1st Author's Affiliation Sony Semiconductor Solutions (SSS)
2nd Author's Name Sachio Akebono  
2nd Author's Affiliation Sony Semiconductor Solutions (SSS)
3rd Author's Name Kazuyoshi Yasuoka  
3rd Author's Affiliation Sony Semiconductor Solutions (SSS)
4th Author's Name Eriko Kato  
4th Author's Affiliation Sony Semiconductor Solutions (SSS)
5th Author's Name Masahiro Tsuruta  
5th Author's Affiliation Sony Semiconductor Solutions (SSS)
6th Author's Name Kensuke Ota  
6th Author's Affiliation Sony Semiconductor Solutions (SSS)
7th Author's Name Kazuki Haraguchi  
7th Author's Affiliation Sony Semiconductor Solutions (SSS)
8th Author's Name Masahiro Watanabe  
8th Author's Affiliation Sony Semiconductor Solutions (SSS)
9th Author's Name Genki Fujii  
9th Author's Affiliation Sony Semiconductor Solutions (SSS)
10th Author's Name Koichiro Yamanaka  
10th Author's Affiliation Sony Semiconductor Solutions (SSS)
11th Author's Name Kazunori Yasuda  
11th Author's Affiliation Sony Semiconductor Solutions (SSS)
12th Author's Name Satoshi Minami  
12th Author's Affiliation Sony Semiconductor Solutions (SSS)
13th Author's Name Katsuhiko Hanzawa  
13th Author's Affiliation Sony Semiconductor Solutions (SSS)
14th Author's Name Kohei Matsuda  
14th Author's Affiliation Sony Semiconductor Solutions (SSS)
15th Author's Name Akihiko Kato  
15th Author's Affiliation Sony Semiconductor Solutions (SSS)
16th Author's Name Yosuke Ueno  
16th Author's Affiliation Sony Semiconductor Solutions (SSS)
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Speaker Author-1 
Date Time 2026-03-27 09:55:00 
Presentation Time 25 minutes 
Registration for IST 
Paper # IST2026-14 
Volume (vol) vol.50 
Number (no) no.14 
Page pp.18-22 
#Pages 5 
Date of Issue 2026-03-20 (IST) 

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