Machine Vision Enabled by Two‐Dimensional Ferroelectric Materials

ABSTRACT Machine vision, a crucial branch of artificial intelligence and computer vision, enables machines to perceive, analyze, and make decisions based on visual data from images or videos. Its basic process includes collecting environmental information with sensors, extracting features with image processing algorithms, and converting information into executable instructions. Two‐dimensional (2D) ferroelectric materials, due to their characteristics such as a surface without dangling bonds, ultrafast polarization switching, room‐temperature bulk photovoltaic effect, and ultra‐low power consumption, perform well in simulating synapses and retinas, and can achieve multi‐state storage and neuromorphic functions. This review examines the application of 2D ferroelectric materials in machine vision. It introduces several representative materials, analyzes various typical device structures, and highlights key achievements of thesse devices in this field. As an emerging class of materials, 2D ferroelectrics hold promise for integrated sensor‐memory‐computing systems, offering new pathways for the advancement of modern electronics.