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Bio-Inspired Artificial Vision and Neuromorphic Image Processing Devices

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Abstract
Remarkable technological developments for efficient image recognition (i.e., image acquisition and image data processing) have been reported in the past decade. Such advances in imaging and image processing technologies have driven significant progress in mobile electronics and machine vision applications. In particular, for image acquisition devices, two types of natural eyes (i.e., chambered and compound eyes) have inspired the development of novel multifunctional imaging devices with unique optical geometries. For image data processing devices, novel computing devices based on memristor crossbar arrays, such as electronic synapses, have been developed. More recently, the integration of imaging and image processing devices in a single unit further enhances the system-level efficiency. Herein, such recent advances in the bio-inspired artificial vision and neuromorphic image processing devices, aimed at providing efficient image recognition, are reviewed. First, various imaging devices inspired by the structural and functional features of natural eyes are introduced. Second, artificial synapses and their operation principles are thoroughly discussed. Third, the neuromorphic vision sensor that integrates the imaging and image processing devices is reviewed. Finally, a brief summary and future outlook are presented.
Author(s)
Kim, Min SungKim, Min SeokLee, Gil JuSunwoo, Sung-HyukChang, SehuiSong, Young MinKim, Dae-Hyeong
Issued Date
2022-02
Type
Article
DOI
10.1002/admt.202100144
URI
https://scholar.gist.ac.kr/handle/local/11053
Publisher
WILEY
Citation
ADVANCED MATERIALS TECHNOLOGIES, v.7, no.2, pp.2100144
ISSN
2365-709X
Appears in Collections:
Department of Electrical Engineering and Computer Science > 1. Journal Articles
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