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The emerging optoelectronic neuromorphic devices are widely concerned due to their capability to integrate the functions of signal sensing, memory, and processing. Although significant advancements have been made in the study of individual optoelectronic synaptic devices, the development of hardware‐level image recognition systems based on photo‐synapse arrays remains a challenge. In this study, a crosstalk‐free, easy‐to‐integrate, and scalable 8 × 8 crossbar array for optical image sensing and storage is demonstrated using vertical two‐terminal ZnO photo‐synapses with the self‐denoising function. By designing peripheral circuits, a complete hardware‐level artificial visual system is constructed that successfully implements the real‐time pattern recognition tasks for 8 × 8 pixel images. The excellent performance of the photo‐synapse array shows its remarkable ability in highly efficient optic neuromorphic computing. Additionally, an in‐sensor reservoir computing (RC) system is constructed for image recognition of handwritten digits. The system achieves a high classification accuracy of 95.1%. [ABSTRACT FROM AUTHOR]

Bio‐inspired machine visions have caused wide attentions due to the higher time/power efficiencies over the conventional architectures. Although bio‐mimic photo‐sensors and neuromorphic computing have been individually demonstrated, a complete monolithic vision system has rarely been studied. Here, a neuromorphic machine vision system (NMVS) integrating front‐end retinomorphic sensors and a back‐end convolutional neural network (CNN) based on a single ferroelectric‐semiconductor‐transistor (FST) device structure is reported. As a photo‐sensor, the FST shows a broadband (275–808 nm) retina‐like light adaption function with a large dynamic range of 20.3 stops, and as a unit of the CNN, the FST's weight can be linearly programmed. In total, the NMVS has a high recognition accuracy of 93.0% on a broadband‐dim‐image classification task, which is 20% higher than that of an incomplete system without the retinomorphic sensors. Because of the monolithic unit, the NVMS shows high feasibility for integrated bio‐inspired machine vision systems. [ABSTRACT FROM AUTHOR]