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IRIS: Integrated Retinal Functionality in Image Sensors

Neuromorphic image sensors draw inspiration from the biological retina to implement visual computations in electronic hardware. Gain control in phototransduction and temporal differentiation at the first retinal synapse inspired the first generation of neuromorphic sensors, but processing in downstr...

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Autores principales: Yin, Zihan, Kaiser, Md Abdullah-Al, Camara, Lamine Ousmane, Camarena, Mark, Parsa, Maryam, Jacob, Ajey, Schwartz, Gregory, Jaiswal, Akhilesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10502419/
https://www.ncbi.nlm.nih.gov/pubmed/37719155
http://dx.doi.org/10.3389/fnins.2023.1241691
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author Yin, Zihan
Kaiser, Md Abdullah-Al
Camara, Lamine Ousmane
Camarena, Mark
Parsa, Maryam
Jacob, Ajey
Schwartz, Gregory
Jaiswal, Akhilesh
author_facet Yin, Zihan
Kaiser, Md Abdullah-Al
Camara, Lamine Ousmane
Camarena, Mark
Parsa, Maryam
Jacob, Ajey
Schwartz, Gregory
Jaiswal, Akhilesh
author_sort Yin, Zihan
collection PubMed
description Neuromorphic image sensors draw inspiration from the biological retina to implement visual computations in electronic hardware. Gain control in phototransduction and temporal differentiation at the first retinal synapse inspired the first generation of neuromorphic sensors, but processing in downstream retinal circuits, much of which has been discovered in the past decade, has not been implemented in image sensor technology. We present a technology-circuit co-design solution that implements two motion computations—object motion sensitivity and looming detection—at the retina's output that could have wide applications for vision-based decision-making in dynamic environments. Our simulations on Globalfoundries 22 nm technology node show that the proposed retina-inspired circuits can be fabricated on image sensing platforms in existing semiconductor foundries by taking advantage of the recent advances in semiconductor chip stacking technology. Integrated Retinal Functionality in Image Sensors (IRIS) technology could drive advances in machine vision applications that demand energy-efficient and low-bandwidth real-time decision-making.
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spelling pubmed-105024192023-09-16 IRIS: Integrated Retinal Functionality in Image Sensors Yin, Zihan Kaiser, Md Abdullah-Al Camara, Lamine Ousmane Camarena, Mark Parsa, Maryam Jacob, Ajey Schwartz, Gregory Jaiswal, Akhilesh Front Neurosci Neuroscience Neuromorphic image sensors draw inspiration from the biological retina to implement visual computations in electronic hardware. Gain control in phototransduction and temporal differentiation at the first retinal synapse inspired the first generation of neuromorphic sensors, but processing in downstream retinal circuits, much of which has been discovered in the past decade, has not been implemented in image sensor technology. We present a technology-circuit co-design solution that implements two motion computations—object motion sensitivity and looming detection—at the retina's output that could have wide applications for vision-based decision-making in dynamic environments. Our simulations on Globalfoundries 22 nm technology node show that the proposed retina-inspired circuits can be fabricated on image sensing platforms in existing semiconductor foundries by taking advantage of the recent advances in semiconductor chip stacking technology. Integrated Retinal Functionality in Image Sensors (IRIS) technology could drive advances in machine vision applications that demand energy-efficient and low-bandwidth real-time decision-making. Frontiers Media S.A. 2023-09-01 /pmc/articles/PMC10502419/ /pubmed/37719155 http://dx.doi.org/10.3389/fnins.2023.1241691 Text en Copyright © 2023 Yin, Kaiser, Camara, Camarena, Parsa, Jacob, Schwartz and Jaiswal. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Yin, Zihan
Kaiser, Md Abdullah-Al
Camara, Lamine Ousmane
Camarena, Mark
Parsa, Maryam
Jacob, Ajey
Schwartz, Gregory
Jaiswal, Akhilesh
IRIS: Integrated Retinal Functionality in Image Sensors
title IRIS: Integrated Retinal Functionality in Image Sensors
title_full IRIS: Integrated Retinal Functionality in Image Sensors
title_fullStr IRIS: Integrated Retinal Functionality in Image Sensors
title_full_unstemmed IRIS: Integrated Retinal Functionality in Image Sensors
title_short IRIS: Integrated Retinal Functionality in Image Sensors
title_sort iris: integrated retinal functionality in image sensors
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10502419/
https://www.ncbi.nlm.nih.gov/pubmed/37719155
http://dx.doi.org/10.3389/fnins.2023.1241691
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