Abstract

AbstractMachine vision technology is a thriving interdisciplinary subject to simulate human vision‐related intelligent behaviors, which has played an increasingly important role in various fields, especially in artificial intelligence and big‐data eras. However, the existing silicon‐based machine vision technology (s‐MVT) has been plagued by complex and inefficient von Neumann architecture, thus gradually becoming overwhelmed when handling high‐throughput parallel tasks. The emerging bionic machine vision technology (b‐MVT) with new materials, working principles, and architectures are attracting ever‐increasing attention, which simulates the structure‐function relationship of the human visual system and shows great potential in processing optical information efficiently with low power consumption. In this review, the recent developments achieved in the b‐MVT are summarized, with a particular emphasis on material selection, device fabrication and performance, as well as several popular neural networks for back‐end image recognition. A summary and critical challenges of the b‐MVT are also discussed.

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