Integration of image preprocessing and recognition functions in an optoelectronic coupling organic ferroelectric retinomorphic neuristor

The human visual system (HVS) has the advantages of a low power consumption and high efficiency because of the synchronous perception and early preprocessing of external image information in the retina, as well as parallel in-memory computing within the visual cortex. Realizing the biofunction simul...

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Vydáno v:Materials horizons Ročník 10; číslo 8; s. 3061
Hlavní autoři: Dai, Qinyong, Pei, Mengjiao, Guo, Jianhang, Wang, Qijing, Hao, Ziqian, Wang, Hengyuan, Li, Yating, Li, Longfei, Lu, Kuakua, Yan, Yang, Shi, Yi, Li, Yun
Médium: Journal Article
Jazyk:angličtina
Vydáno: England 31.07.2023
ISSN:2051-6355, 2051-6355
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Shrnutí:The human visual system (HVS) has the advantages of a low power consumption and high efficiency because of the synchronous perception and early preprocessing of external image information in the retina, as well as parallel in-memory computing within the visual cortex. Realizing the biofunction simulation of the retina and visual cortex in a single device structure provides opportunities for performance improvements and machine vision system (MVS) integration. Here, we fabricate organic ferroelectric retinomorphic neuristors that integrate the retina-like preprocessing function and recognition of the visual cortex in a single device architecture. Benefiting from the electrical/optical coupling modulation of ferroelectric polarization, our devices show a bidirectional photoresponse that acts as the basis for mimicking retinal preconditioning and multi-level memory capabilities for recognition. The MVS based on the proposed retinomorphic neuristors achieves a high recognition accuracy of ∼90%, which is 20% higher than that of the incomplete system without the preprocessing function. In addition, we successfully demonstrate image encryption and optical programming logic gate functions. Our work suggests that the proposed retinomorphic neuristors offer great potential for MVS monolithic integration and functional expansion.
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ISSN:2051-6355
2051-6355
DOI:10.1039/d3mh00429e