To conduct further image processing requires that a large amount of image data be transferred repeatedly between the memory and the processor, resulting in high energy consumption. 17 Visual information is obtained through image sensors in the MVS and stored in a storage module. The image acquisition, storage, and processing modules in traditional von Neumann structures are physically separated. ![]() 15, 16 However, an MVS based on von Neumann architecture encounters difficulties when applied to new scenarios with higher performance requirements. 11, 14Ĭombining 2D materials with silicon chips to form a heterogeneous structure platform based on vdW forces can greatly promote vertical integration and functional diversification. 13 Because different layers of 2D materials are bonded by van der Waals forces, with no dangling bonds, they can be easily integrated with each other or memristor circuits, regardless of lattice mismatch or deposition temperature. 12 Because they are so thin, their band structure can be adjusted through a localized electric field or external stress thus, their detection waveband can range from ultraviolet to terahertz. 11 2D materials are a large family, including metals, semi-metals, semiconductors, and insulators. 6- 10 Their extreme thinness, quantum electronic states, large carrier mobility, and localized optical transition give them many advantages over traditional materials. 5 In recent years, two-dimensional (2D) materials (i.e., materials with atomically thin layers) have become a powerful competitor. 3 Infrared photosensor materials include cooled mercury-cadmium-telluride (MCT), InSb, quantum wells, Type-II superlattice or uncooled VO x, PbS, InGaAs, amorphous silicon, PbS, and PbSe. ![]() At present, most commercial visible-image sensors are either charge-coupled devices (CCDs) or CMOS image sensors (CISs). Image acquisition by an MVS depends on the image sensor. ![]() 2 New application scenarios and increasing quantities of data have created a demand for MVSs with faster parallel processing, higher energy efficiency, smaller volume, and lower price. 3 With the rapid development of information integration, machine vision has become indispensable in automated production, autonomous driving, robotics, security, and other domains. 1, 2 They can be used for image acquisition, image processing, and feature recognition. Machine vision systems (MVSs) simulate human visual functions to observe and recognize the objective world.
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