Photoelectric Memristor-Based Machine Vision for Artificial Intelligence Applications

记忆电阻器 冯·诺依曼建筑 光电效应 人工智能 计算机科学 光电传感器 人工智能应用 机器视觉 计算机视觉 工程类 物理 光学 电气工程 电子工程 操作系统
作者
Chuan Yang,Bai Sun,Guangdong Zhou,Tao Guo,Chuan Ke,Yuanzheng Chen,Jinyou Shao,Yong Zhao,Hongyan Wang
出处
期刊:ACS materials letters [American Chemical Society]
卷期号:5 (2): 504-526 被引量:52
标识
DOI:10.1021/acsmaterialslett.2c00911
摘要

With the rapid development of next-generation artificial intelligence technology, research on advanced machine vision has received extensive attention. It is well-known that significant progress has been made in artificial vision systems based on light sensors, but the separate light sensor and memory require additional time for information transfer to realize computation due to the limitation of the von Neumann architecture, which delays the computational speed and hinders large-scale integration. In recent years, the emergence of photoelectric memristors has brought new inspiration to the study of machine vision, which is expected to overcome the above problems. Photoelectric memristors can not only respond directly to light stimuli but also perform temporary memory and real-time processing of visual information and sensory data, providing a promising hardware foundation for the development of artificial vision systems. In this review, the background and related theory of photoelectric memristors and machine vision are first introduced. Then, the research progress of photoelectric memristors and machine vision based on them is reviewed. Finally, the existing problems impeding the progress of machine vision based on photoelectric memristors are summarized, and the future development is predicted.
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