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Nanomaterial-Based Synaptic Optoelectronic Devices for In-Sensor Preprocessing of Image Data
[Image: see text] With the advance in information technologies involving machine vision applications, the demand for energy- and time-efficient acquisition, transfer, and processing of a large amount of image data has rapidly increased. However, current architectures of the machine vision system hav...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9933102/ https://www.ncbi.nlm.nih.gov/pubmed/36816688 http://dx.doi.org/10.1021/acsomega.3c00440 |
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author | Lee, Minkyung Seung, Hyojin Kwon, Jong Ik Choi, Moon Kee Kim, Dae-Hyeong Choi, Changsoon |
author_facet | Lee, Minkyung Seung, Hyojin Kwon, Jong Ik Choi, Moon Kee Kim, Dae-Hyeong Choi, Changsoon |
author_sort | Lee, Minkyung |
collection | PubMed |
description | [Image: see text] With the advance in information technologies involving machine vision applications, the demand for energy- and time-efficient acquisition, transfer, and processing of a large amount of image data has rapidly increased. However, current architectures of the machine vision system have inherent limitations in terms of power consumption and data latency owing to the physical isolation of image sensors and processors. Meanwhile, synaptic optoelectronic devices that exhibit photoresponse similar to the behaviors of the human synapse enable in-sensor preprocessing, which makes the front-end part of the image recognition process more efficient. Herein, we review recent progress in the development of synaptic optoelectronic devices using functional nanomaterials and their unique interfacial characteristics. First, we provide an overview of representative functional nanomaterials and device configurations for the synaptic optoelectronic devices. Then, we discuss the underlying physics of each nanomaterial in the synaptic optoelectronic device and explain related device characteristics that allow for the in-sensor preprocessing. We also discuss advantages achieved by the application of the synaptic optoelectronic devices to image preprocessing, such as contrast enhancement and image filtering. Finally, we conclude this review and present a short prospect. |
format | Online Article Text |
id | pubmed-9933102 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-99331022023-02-17 Nanomaterial-Based Synaptic Optoelectronic Devices for In-Sensor Preprocessing of Image Data Lee, Minkyung Seung, Hyojin Kwon, Jong Ik Choi, Moon Kee Kim, Dae-Hyeong Choi, Changsoon ACS Omega [Image: see text] With the advance in information technologies involving machine vision applications, the demand for energy- and time-efficient acquisition, transfer, and processing of a large amount of image data has rapidly increased. However, current architectures of the machine vision system have inherent limitations in terms of power consumption and data latency owing to the physical isolation of image sensors and processors. Meanwhile, synaptic optoelectronic devices that exhibit photoresponse similar to the behaviors of the human synapse enable in-sensor preprocessing, which makes the front-end part of the image recognition process more efficient. Herein, we review recent progress in the development of synaptic optoelectronic devices using functional nanomaterials and their unique interfacial characteristics. First, we provide an overview of representative functional nanomaterials and device configurations for the synaptic optoelectronic devices. Then, we discuss the underlying physics of each nanomaterial in the synaptic optoelectronic device and explain related device characteristics that allow for the in-sensor preprocessing. We also discuss advantages achieved by the application of the synaptic optoelectronic devices to image preprocessing, such as contrast enhancement and image filtering. Finally, we conclude this review and present a short prospect. American Chemical Society 2023-02-03 /pmc/articles/PMC9933102/ /pubmed/36816688 http://dx.doi.org/10.1021/acsomega.3c00440 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Lee, Minkyung Seung, Hyojin Kwon, Jong Ik Choi, Moon Kee Kim, Dae-Hyeong Choi, Changsoon Nanomaterial-Based Synaptic Optoelectronic Devices for In-Sensor Preprocessing of Image Data |
title | Nanomaterial-Based
Synaptic Optoelectronic Devices
for In-Sensor Preprocessing of Image Data |
title_full | Nanomaterial-Based
Synaptic Optoelectronic Devices
for In-Sensor Preprocessing of Image Data |
title_fullStr | Nanomaterial-Based
Synaptic Optoelectronic Devices
for In-Sensor Preprocessing of Image Data |
title_full_unstemmed | Nanomaterial-Based
Synaptic Optoelectronic Devices
for In-Sensor Preprocessing of Image Data |
title_short | Nanomaterial-Based
Synaptic Optoelectronic Devices
for In-Sensor Preprocessing of Image Data |
title_sort | nanomaterial-based
synaptic optoelectronic devices
for in-sensor preprocessing of image data |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9933102/ https://www.ncbi.nlm.nih.gov/pubmed/36816688 http://dx.doi.org/10.1021/acsomega.3c00440 |
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