关于非冯诺依曼柔性神经形态视觉传感器

IF 12.3 1区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC npj Flexible Electronics Pub Date : 2024-05-07 DOI:10.1038/s41528-024-00313-3
Hao Wang, Bin Sun, Shuzhi Sam Ge, Jie Su, Ming Liang Jin
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引用次数: 0

摘要

人类视觉系统的结构和机理蕴含着丰富的宝藏,模拟人类视觉系统可以获得令人惊喜的效果。本文从人类视觉系统出发,比较和讨论了人类视觉系统与传统机器视觉系统之间的差异。鉴于视觉信息种类繁多、数量庞大,使用非冯-诺依曼结构、灵活的神经形态视觉传感器可以有效弥补基于冯-诺依曼架构的传统机器视觉系统的局限性。首先,本文针对视网膜功能的仿真,概述了非冯-诺依曼计算架构的原理和电路实现方法。其次,在模拟视网膜表面结构方面,本文介绍了柔性传感器阵列的制造方法。最后,本文分析了非冯诺依曼柔性神经形态视觉传感器目前面临的挑战,并对其未来发展提出了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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On non-von Neumann flexible neuromorphic vision sensors
The structure and mechanism of the human visual system contain rich treasures, and surprising effects can be achieved by simulating the human visual system. In this article, starting from the human visual system, we compare and discuss the discrepancies between the human visual system and traditional machine vision systems. Given the wide variety and large volume of visual information, the use of non-von Neumann structured, flexible neuromorphic vision sensors can effectively compensate for the limitations of traditional machine vision systems based on the von Neumann architecture. Firstly, this article addresses the emulation of retinal functionality and provides an overview of the principles and circuit implementation methods of non-von Neumann computing architectures. Secondly, in terms of mimicking the retinal surface structure, this article introduces the fabrication approach for flexible sensor arrays. Finally, this article analyzes the challenges currently faced by non-von Neumann flexible neuromorphic vision sensors and offers a perspective on their future development.
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来源期刊
CiteScore
17.10
自引率
4.80%
发文量
91
审稿时长
6 weeks
期刊介绍: npj Flexible Electronics is an online-only and open access journal, which publishes high-quality papers related to flexible electronic systems, including plastic electronics and emerging materials, new device design and fabrication technologies, and applications.
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