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Next‐generation machine vision systems incorporating two‐dimensional materials: Progress and perspectives

Peisong Wu, Ting He, He Zhu, Yang Wang, Qing Li, Zhen Wang, Xiao Fu, Fang Wang, Peng Wang, Chongxin Shan, Zhiyong Fan, Lei Liao, Peng Zhou, Weida Hu

Year
2021
Citations
117
Access
Open access

Abstract

Abstract Machine vision systems (MVSs) are an important component of intelligent systems, such as autonomous vehicles and robots. However, with the continuous increase in data and new application scenarios, new requirements are put forward for the next generation of MVS. There is an urgent need to find new material systems to complement the existing semiconductor technology based on thin‐film materials, and new architectures must be explored to improve efficiency. Because of their unique physical properties, two‐dimensional (2D) materials have received extensive attention for use in MVSs, especially in biomimetic ones: the human visual system, which can process complex visual information with low power consumption, provides a model for next‐generation MVSs. This review paper summarizes the progress and challenges of applying 2D material photodetectors in sense‐memory‐computational integration and biomimetic image sensors for machine vision. image

Keywords

Computer scienceMachine visionProcess (computing)Component (thermodynamics)Artificial intelligenceRobotSystems engineeringHuman–computer interactionEngineering

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