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视觉通路的层级结构:功能与受启发的人工视觉。

Hierarchies in Visual Pathway: Functions and Inspired Artificial Vision.

机构信息

Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China.

College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, P. R. China.

出版信息

Adv Mater. 2024 Feb;36(6):e2301986. doi: 10.1002/adma.202301986. Epub 2023 Nov 30.

Abstract

The development of artificial intelligence has posed a challenge to machine vision based on conventional complementary metal-oxide semiconductor (CMOS) circuits owing to its high latency and inefficient power consumption originating from the data shuffling between memory and computation units. Gaining more insights into the function of every part of the visual pathway for visual perception can bring the capabilities of machine vision in terms of robustness and generality. Hardware acceleration of more energy-efficient and biorealistic artificial vision highly necessitates neuromorphic devices and circuits that are able to mimic the function of each part of the visual pathway. In this paper, we review the structure and function of the entire class of visual neurons from the retina to the primate visual cortex within reach (Chapter 2) are reviewed. Based on the extraction of biological principles, the recent hardware-implemented visual neurons located in different parts of the visual pathway are discussed in detail in Chapters 3 and 4. Furthermore, valuable applications of inspired artificial vision in different scenarios (Chapter 5) are provided. The functional description of the visual pathway and its inspired neuromorphic devices/circuits are expected to provide valuable insights for the design of next-generation artificial visual perception systems.

摘要

人工智能的发展对基于传统互补金属氧化物半导体(CMOS)电路的机器视觉提出了挑战,因为其数据在存储单元和计算单元之间的大量数据搬运导致了高延迟和低效率的功耗。深入了解视觉感知的视觉通路的每个部分的功能,可以提高机器视觉在鲁棒性和通用性方面的能力。为了实现更节能和更逼真的人工视觉的硬件加速,非常需要能够模拟视觉通路各个部分功能的神经形态器件和电路。在本文中,我们回顾了从视网膜到灵长类动物视觉皮层的整个视觉神经元类别的结构和功能(第 2 章)。基于对生物原理的提取,第 3 章和第 4 章详细讨论了位于视觉通路不同部分的最近已实现的硬件视觉神经元。此外,还提供了受启发的人工视觉在不同场景中的有价值的应用(第 5 章)。视觉通路及其受启发的神经形态器件/电路的功能描述,有望为下一代人工视觉感知系统的设计提供有价值的见解。

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