Retina-Inspired Artificial Optoelectronic Neurons With Broad Spectral Response for Visual Image Pre-Processing

IF 4.1 2区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Electron Device Letters Pub Date : 2025-01-09 DOI:10.1109/LED.2024.3525088

Guocheng Zhang;Jianchuan Tang;Binglin Lai;Hongyu Wang;Zili Zeng;Changqiang Su;Xin Yi;Yujie Yan;Huipeng Chen

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引用次数: 0

Abstract

Inspired by the human retina, the development of neuromorphic vision systems featuring image perception, memory, and processing functions aims to address the limitations of traditional artificial vision systems concerning circuit simplification, device integration, and power consumption. The narrow spectral response of optoelectronic neurons, an important hardware basis for neuromorphic vision systems, limits their application in broad-spectrum artificial visual perception. In this study, we present an artificial optoelectronic neuron that demonstrates broadband sensing capabilities with a response range encompassing ultraviolet, visible, and near-infrared regions. Furthermore, we have designed a

$64\times 64$

array of optoelectronic neurons capable of effectively simulating the light perception and image pre-processing functions (enhance image contrast), of the retina. This work is important for improving image processing efficiency and realizing neuromorphic vision systems with broadband perception.

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视网膜激发的具有广谱响应的人工光电神经元用于视觉图像预处理

受人类视网膜的启发，具有图像感知、记忆和处理功能的神经形态视觉系统的发展旨在解决传统人工视觉系统在电路简化、设备集成和功耗方面的局限性。光电神经元的窄谱响应是神经形态视觉系统的重要硬件基础，限制了其在广谱人工视觉感知中的应用。在这项研究中，我们提出了一种人工光电神经元，它展示了宽带传感能力，响应范围包括紫外线、可见光和近红外区域。此外，我们还设计了一个$64 × 64$的光电神经元阵列，能够有效地模拟视网膜的光感知和图像预处理功能（增强图像对比度）。这项工作对于提高图像处理效率和实现具有宽带感知的神经形态视觉系统具有重要意义。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Electron Device Letters 工程技术-工程：电子与电气

CiteScore

8.20

自引率

10.20%

发文量

551

审稿时长

1.4 months

期刊介绍： IEEE Electron Device Letters publishes original and significant contributions relating to the theory, modeling, design, performance and reliability of electron and ion integrated circuit devices and interconnects, involving insulators, metals, organic materials, micro-plasmas, semiconductors, quantum-effect structures, vacuum devices, and emerging materials with applications in bioelectronics, biomedical electronics, computation, communications, displays, microelectromechanics, imaging, micro-actuators, nanoelectronics, optoelectronics, photovoltaics, power ICs and micro-sensors.