Photoelectric Memristor-Based Machine Vision for Artificial Intelligence Applications

• Published in: ACS materials letters 2023-02, Vol.5 (2), p.504-526
• Main Authors: Yang, Chuan, Sun, Bai, Zhou, Guangdong, Guo, Tao, Ke, Chuan, Chen, Yuanzheng, Shao, Jinyou, Zhao, Yong, Wang, Hongyan
• Format: Article
• Language: English
• ISSN: 2639-4979; 2639-4979
• DOI: 10.1021/acsmaterialslett.2c00911

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.