Imprinting vision as memory is a core attribute of human cognitive learning. Fundamental to artificial intelligence systems are bioinspired neuromorphic vision components for the visible and invisible segments of the electromagnetic spectrum. Realization of a single imaging unit with a combination of in‐built memory and signal processing capability is imperative to deploy efficient brain‐like vision systems. However, the lack of a platform that can be fully controlled by light without the need to apply alternating polarity electric signals has hampered this technological advance. Here, a neuromorphic imaging element based on a fully light‐modulated 2D semiconductor in a simple reconfigurable phototransistor structure is presented. This standalone device exhibits inherent characteristics that enable neuromorphic image pre‐processing and recognition. Fundamentally, the unique photoresponse induced by oxidation‐related defects in 2D black phosphorus (BP) is exploited to achieve visual memory, wavelength‐selective multibit programming, and erasing functions, which allow in‐pixel image pre‐processing. Furthermore, all‐optically driven neuromorphic computation is demonstrated by machine learning to classify numbers and recognize images with an accuracy of over 90%. The devices provide a promising approach toward neurorobotics, human–machine interaction technologies, and scalable bionic systems with visual data storage/buffering and processing.

中文翻译：

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层状黑磷中的完全光控记忆和神经形态计算

将视觉作为记忆印记是人类认知学习的核心属性。人工智能系统的基础是生物启发的神经形态视觉组件，用于电磁频谱的可见和不可见部分。必须结合内置内存和信号处理功能来实现单个成像单元，以部署高效的类似于大脑的视觉系统。然而，缺乏可以通过光完全控制而不需要施加交变极性电信号的平台阻碍了该技术的进步。在这里，提出了一种神经形态成像元件，该元件基于简单可重构光电晶体管结构中的全光调制2D半导体。这种独立的设备具有可实现神经形态图像预处理和识别的固有特性。从根本上说，利用二维黑磷（BP）中与氧化有关的缺陷引起的独特光响应来实现视觉记忆，波长选择性多位编程和擦除功能，从而可以进行像素内图像预处理。此外，机器学习证明了全光学驱动的神经形态计算可以对数字进行分类并以超过90％的精度识别图像。这些设备为神经机器人技术，人机交互技术以及具有可视数据存储/缓冲和处理功能的可扩展仿生系统提供了一种有前途的方法。此外，机器学习证明了全光学驱动的神经形态计算可以对数字进行分类并以超过90％的精度识别图像。这些设备为神经机器人技术，人机交互技术以及具有可视数据存储/缓冲和处理功能的可扩展仿生系统提供了一种有前途的方法。此外，机器学习证明了全光学驱动的神经形态计算可以对数字进行分类并以超过90％的精度识别图像。这些设备为神经机器人技术，人机交互技术以及具有可视数据存储/缓冲和处理功能的可扩展仿生系统提供了一种有前途的方法。