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Retinomorphic optoelectronic devices for intelligent machine vision

Biological visual system can efficiently handle optical information within the retina and visual cortex of the brain, which suggests an alternative approach for the upgrading of the current low-intelligence, large energy consumption, and complex circuitry of the artificial vision system for high-per...

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Detalles Bibliográficos
Autores principales: Chen, Weilin, Zhang, Zhang, Liu, Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8762475/
https://www.ncbi.nlm.nih.gov/pubmed/35072015
http://dx.doi.org/10.1016/j.isci.2021.103729
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author Chen, Weilin
Zhang, Zhang
Liu, Gang
author_facet Chen, Weilin
Zhang, Zhang
Liu, Gang
author_sort Chen, Weilin
collection PubMed
description Biological visual system can efficiently handle optical information within the retina and visual cortex of the brain, which suggests an alternative approach for the upgrading of the current low-intelligence, large energy consumption, and complex circuitry of the artificial vision system for high-performance edge computing applications. In recent years, retinomorphic machine vision based on the integration of optoelectronic image sensors and processors has been regarded as a promising candidate to improve this phenomenon. This novel intelligent machine vision technology can perform information preprocessing near or even within the sensor in the front end, thereby reducing the transmission of redundant raw data and improving the efficiency of the back-end processor for high-level computing tasks. In this contribution, we try to present a comprehensive review on the recent progress achieved in this emergent field.
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spelling pubmed-87624752022-01-20 Retinomorphic optoelectronic devices for intelligent machine vision Chen, Weilin Zhang, Zhang Liu, Gang iScience Review Biological visual system can efficiently handle optical information within the retina and visual cortex of the brain, which suggests an alternative approach for the upgrading of the current low-intelligence, large energy consumption, and complex circuitry of the artificial vision system for high-performance edge computing applications. In recent years, retinomorphic machine vision based on the integration of optoelectronic image sensors and processors has been regarded as a promising candidate to improve this phenomenon. This novel intelligent machine vision technology can perform information preprocessing near or even within the sensor in the front end, thereby reducing the transmission of redundant raw data and improving the efficiency of the back-end processor for high-level computing tasks. In this contribution, we try to present a comprehensive review on the recent progress achieved in this emergent field. Elsevier 2022-01-01 /pmc/articles/PMC8762475/ /pubmed/35072015 http://dx.doi.org/10.1016/j.isci.2021.103729 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Chen, Weilin
Zhang, Zhang
Liu, Gang
Retinomorphic optoelectronic devices for intelligent machine vision
title Retinomorphic optoelectronic devices for intelligent machine vision
title_full Retinomorphic optoelectronic devices for intelligent machine vision
title_fullStr Retinomorphic optoelectronic devices for intelligent machine vision
title_full_unstemmed Retinomorphic optoelectronic devices for intelligent machine vision
title_short Retinomorphic optoelectronic devices for intelligent machine vision
title_sort retinomorphic optoelectronic devices for intelligent machine vision
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8762475/
https://www.ncbi.nlm.nih.gov/pubmed/35072015
http://dx.doi.org/10.1016/j.isci.2021.103729
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