Evidence map›Paper›PMID 41194404›Full record

ReviewAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Devices, Functions, and Applications of Artificial Neuromorphic Visual Systems.

Jiaxin Liu, Bo Li, Chi Liu, Dongming Sun, Huiming Cheng

Abstract readReview
In one paragraph

Review in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Devices, Functions, and Applications of Artificial Neuromorphic Visual Systems.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jiaxin LiuSchool of Material Science and Engineering, University of Science and Technology of China, 72 Wenhua Road, Shenyang, 110016, P. R. China.
Bo LiShenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, 72 Wenhua Road, Shenyang, 110016, P. R. China.
Chi LiuSchool of Material Science and Engineering, University of Science and Technology of China, 72 Wenhua Road, Shenyang, 110016, P. R. China.
Dongming SunSchool of Material Science and Engineering, University of Science and Technology of China, 72 Wenhua Road, Shenyang, 110016, P. R. China.ORCID https://orcid.org/0000-0003-1552-7940
Huiming ChengSchool of Material Science and Engineering, University of Science and Technology of China, 72 Wenhua Road, Shenyang, 110016, P. R. China.

Funding

Artificial Intelligence Technology Innovation Project of Liaoning Province 2023JH26/10300019China Postdoctoral Science Foundation 2023M733574China Postdoctoral Science Foundation 2024T170946China Postdoctoral Science Foundation under Grant Number GZB20230776Excellent Youth Fund Project of Liaoning Province 2023JH3/10200003Liaoning Provincial Key Laboratory of Public Opinion and Network Security Information System d252453002National Key Research and Development Program of China 2021YFA1200801National Natural Science Foundation of China 52188101National Natural Science Foundation of China 62074150National Natural Science Foundation of China 62125406National Natural Science Foundation of China 62450124National Natural Science Foundation of China 62504228National Natural Science Foundation of China E311L5191ROutstanding Youth Fund Project of Liaoning Province 2025JH6/101100015Special Projects of the Central Government in Guidance of Local Science and Technology Development 2024010859-JH6/1006Special Research Assistantship Project of the Chinese Academy of Sciences E455L502
6 · The paper itself

Abstract

Artificial neuromorphic vision systems emulate the biological visual pathway by integrating sensing, storage, and information processing within a unified architecture. Featuring high speed, low power consumption, and superior temporal resolution, they demonstrate significant potential in fields such as autonomous driving, facial recognition, and intelligent perception. As the core building block, the optoelectronic synapse plays a decisive role in determining system performance, which is closely related to its material composition, structural design, and functional characteristics. This review systematically summarizes recent progress in optoelectronic synaptic materials, device architectures, and performance evaluation methodologies. Furthermore, it explores the working mechanisms and network architectures of optoelectronic synapse-based neuromorphic vision systems, highlighting their capability in image perception, information storage, and target recognition. Current challenges, including environmental stability, large-scale array fabrication, chip-level integration, and adaptability of visual functions to real-world scenarios, are discussed in depth. Finally, the review provides an outlook on future development trends toward stable, scalable, and highly integrated optoelectronic neural vision systems, underscoring their key importance in next-generation intelligent sensing and information-processing technologies.

Indexed as

functions and applicationsneuromorphic visual systemsoptoelectronic synapsessynaptic materials and structuressynaptic performance metrics

Identifiers

PMID41194404
PMCPMC12697879

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.