Evidence map›Paper›PMID 38503787›Full record

ArticleNature communications2024

High performance artificial visual perception and recognition with a plasmon-enhanced 2D material neural network.

Tian Zhang, Xin Guo, Pan Wang, Xinyi Fan, Zichen Wang, Yan Tong, Decheng Wang, Limin Tong, Linjun Li

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Devices, Functions, and Applications of Artificial Neuromorphic Visual Systems.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  9. A Floating-Gate Photoelectric Synaptic Transistor Utilizing BP/POAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Enhancing 2D Photonics and Optoelectronics with Artificial Microstructures.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    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

9 authors.

Tian ZhangState Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310027, China.ORCID http://orcid.org/0000-0002-8475-7208
Xin GuoState Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310027, China.
Pan WangState Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310027, China.ORCID http://orcid.org/0000-0003-4209-5186
Xinyi FanState Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310027, China.
Zichen WangState Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310027, China.
Yan TongState Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310027, China.
Decheng WangState Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310027, China.
Limin TongState Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310027, China.
Linjun LiState Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310027, China. lilinjun@zju.edu.cn.ORCID http://orcid.org/0000-0002-2734-0414

Funding

National Science Foundation of China | Key Programme 2019YFA0308602National Science Foundation of China | Major Research Plan 91950205Natural Science Foundation of Zhejiang Province (Zhejiang Provincial Natural Science Foundation) LR20A040002
6 · The paper itself

Abstract

The development of neuromorphic visual systems has recently gained momentum due to their potential in areas such as autonomous vehicles and robotics. However, current machine visual systems based on silicon technology usually contain photosensor arrays, format conversion, memory and processing modules. As a result, the redundant data shuttling between each unit, resulting in large latency and high-power consumption, seriously limits the performance of neuromorphic vision chips. Here, we demonstrate an artificial neural network (ANN) architecture based on an integrated 2D MoS

Identifiers

PMID38503787
PMCPMC10951348

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.