Metal Oxide‐Based Neuromorphic Artificial Visual Perception Devices and Systems for Information Perception, Memory and Processing

Abstract Vision is recognized as a critical source of environmental perception for humans, with 80% of information sourced visually. The development of sensors that approach or even surpass human visual capabilities has been a continuous pursuit by researchers and is crucial for advancing fields such as autonomous driving and intelligent security. Recently, neuromorphic devices based on metal oxides have become a focal point of research in biomimetic visual perception due to their sensing, storage, and logical computation advantages. This review introduces the distinct characteristics of human vision, traditional image system, and neuromorphic vision system. Then, the classification, material properties, potential mechanisms, and strategies for enhancing stability of metal oxide‐based neuromorphic devices are systematically discussed. Finally, the applications of neuromorphic vision systems in image memory and enhancement, motion trajectory, depth perception, vision impairment, and recovery are presented, with a projection on the future development of neuromorphic visual systems. This review aims to provide significant reference and guidance for the future advancement of neuromorphic devices in the fields of biomimetic visual perception, humanoid robots, and autonomous driving.

Authors

Institutions

Publication Details

Journal
Advanced Functional Materials
Published
2025-08-05
DOI
https://doi.org/10.1002/adfm.202515213
Citations
11
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
8.03

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Metal Oxide‐Based Neuromorphic Artificial Visual Perception Devices and Systems for Information Perception, Memory and Processing

Jun‐Ge Liang, Yongwoo Jang, Fan Yang, Cong Wang et al.
11 citations
Advanced Functional Materials
Advanced Memory and Neural Computing
8.03
article

Metal Oxide‐Based Neuromorphic Artificial Visual Perception Devices and Systems for Information Perception, Memory and Processing

Jun‐Ge Liang, Yongwoo Jang, Fan Yang, Cong Wang, Yang Li
article en
11 citations

Abstract

Abstract Vision is recognized as a critical source of environmental perception for humans, with 80% of information sourced visually. The development of sensors that approach or even surpass human visual capabilities has been a continuous pursuit by researchers and is crucial for advancing fields such as autonomous driving and intelligent security. Recently, neuromorphic devices based on metal oxides have become a focal point of research in biomimetic visual perception due to their sensing, storage, and logical computation advantages. This review introduces the distinct characteristics of human vision, traditional image system, and neuromorphic vision system. Then, the classification, material properties, potential mechanisms, and strategies for enhancing stability of metal oxide‐based neuromorphic devices are systematically discussed. Finally, the applications of neuromorphic vision systems in image memory and enhancement, motion trajectory, depth perception, vision impairment, and recovery are presented, with a projection on the future development of neuromorphic visual systems. This review aims to provide significant reference and guidance for the future advancement of neuromorphic devices in the fields of biomimetic visual perception, humanoid robots, and autonomous driving.

Advanced Functional MaterialsVol. 36(4)
Shandong University (CN), Kwangwoon University (KR), Harbin Institute of Technology (CN), Hanyang University Medical Center (KR), Hanyang University (KR)
National Natural Science Foundation of China
Openalex Percentile: Top 2%
Advanced Memory and Neural Computing
8.03
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.