Tomohiro Yamazaki, H. Katayama, S. Uehara, Atsushi Nose, M. Kobayashi, Sayaka Shida, Masaki Odahara, Kenichi Takamiya, Yasuaki Hisamatsu, S. Matsumoto, Leo Miyashita, Yoshihiro Watanabe, Takashi Izawa, Y. Muramatsu, M. Ishikawa
{"title":"4.9 1ms高速视觉芯片,采用3d堆叠140GOPS柱平行pe进行时空图像处理","authors":"Tomohiro Yamazaki, H. Katayama, S. Uehara, Atsushi Nose, M. Kobayashi, Sayaka Shida, Masaki Odahara, Kenichi Takamiya, Yasuaki Hisamatsu, S. Matsumoto, Leo Miyashita, Yoshihiro Watanabe, Takashi Izawa, Y. Muramatsu, M. Ishikawa","doi":"10.1109/ISSCC.2017.7870271","DOIUrl":null,"url":null,"abstract":"High-speed vision systems that combine high-frame-rate imaging and highly parallel signal processing enable instantaneous visual feedback to rapidly control machines over human-visual-recognition speeds. Such systems also enable a reduction in circuit scale by using a fast and simple algorithm optimized for high-frame-rate processing [1]. Previous studies on vision systems and chips [1–4] have yielded low imaging performance due to large matrix-based processing element (PE) parallelization [1–3], and low functionality of the limited-purpose column-parallel PE architecture [4], constraining vision-chip applications.","PeriodicalId":269679,"journal":{"name":"2017 IEEE International Solid-State Circuits Conference (ISSCC)","volume":"171 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"53","resultStr":"{\"title\":\"4.9 A 1ms high-speed vision chip with 3D-stacked 140GOPS column-parallel PEs for spatio-temporal image processing\",\"authors\":\"Tomohiro Yamazaki, H. Katayama, S. Uehara, Atsushi Nose, M. Kobayashi, Sayaka Shida, Masaki Odahara, Kenichi Takamiya, Yasuaki Hisamatsu, S. Matsumoto, Leo Miyashita, Yoshihiro Watanabe, Takashi Izawa, Y. Muramatsu, M. Ishikawa\",\"doi\":\"10.1109/ISSCC.2017.7870271\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High-speed vision systems that combine high-frame-rate imaging and highly parallel signal processing enable instantaneous visual feedback to rapidly control machines over human-visual-recognition speeds. Such systems also enable a reduction in circuit scale by using a fast and simple algorithm optimized for high-frame-rate processing [1]. Previous studies on vision systems and chips [1–4] have yielded low imaging performance due to large matrix-based processing element (PE) parallelization [1–3], and low functionality of the limited-purpose column-parallel PE architecture [4], constraining vision-chip applications.\",\"PeriodicalId\":269679,\"journal\":{\"name\":\"2017 IEEE International Solid-State Circuits Conference (ISSCC)\",\"volume\":\"171 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"53\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Solid-State Circuits Conference (ISSCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSCC.2017.7870271\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Solid-State Circuits Conference (ISSCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSCC.2017.7870271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
4.9 A 1ms high-speed vision chip with 3D-stacked 140GOPS column-parallel PEs for spatio-temporal image processing
High-speed vision systems that combine high-frame-rate imaging and highly parallel signal processing enable instantaneous visual feedback to rapidly control machines over human-visual-recognition speeds. Such systems also enable a reduction in circuit scale by using a fast and simple algorithm optimized for high-frame-rate processing [1]. Previous studies on vision systems and chips [1–4] have yielded low imaging performance due to large matrix-based processing element (PE) parallelization [1–3], and low functionality of the limited-purpose column-parallel PE architecture [4], constraining vision-chip applications.