神经形态工程学
材料科学
纳米线
光电导性
单色
光电子学
硫系化合物
碲
图像传感器
晶体管
图像处理
纳米技术
预处理器
噪音(视频)
发光二极管
硅
图像(数学)
电致发光
机器视觉
计算机科学
人工智能
数字图像处理
硅纳米线
响应时间
全息术
作者
Jeehoon Kim,Mose Park,Seung‐Han Kang,Dong‐Won Kang,Sung Kyu Park,Hoo‐Jeong Lee,Yong‐Hoon Kim
标识
DOI:10.1002/adfm.202525952
摘要
Abstract As demand for intelligent machine vision systems grows across diverse fields, neuromorphic computational approaches such as image preprocessing have become crucial for efficient visual processing. Inspired by the biological retina, in‐sensor computational systems offer intrinsic efficiency but have largely depended on multi‐wavelength strategies for optoelectronic contrast enhancement. Here, retina‐mimetic Al 2 O 3 ‐encapsulated tellurium nanowire in‐sensor neuromorphic transistors are introduced for image preprocessing. Interestingly, these devices exhibit gate‐tunable positive and negative photoconductivity under monochromatic illumination, closely resembling retinal visual processing, such as the bidirectional excitatory/inhibitory behavior. The trap‐assisted recombination model, governed by gate polarity, elucidates this gate‐bias tunability. Furthermore, bio‐inspired image preprocessing under varying noise levels resulted in substantial improvements in recognition, ≈93.01% for the weak‐noise and 69.01% strong‐noise case, highlighting the promise of chalcogenide nanowire devices for highly biomimetic artificial vision systems.
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