Evidence map›Paper›PMID 42816499›Full record

ArticleNature communications2026

In-sensor multispectral perception for near- and mid-infrared discrimination.

Shi Fang, Fakun Wang, Fengqi Cui, Jinyang Huang, Wenduo Chen, Chao Han, Hui Ma, Jianbo Yu, Zhenhan Zhang, Chongwu Wang and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Shi Fang *School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore.ORCID http://orcid.org/0000-0001-9255-1579
Fakun Wang *School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore.ORCID http://orcid.org/0009-0006-7958-605X
Fengqi CuiInstitute of Advanced Technology, University of Science and Technology of China, Hefei, China.ORCID http://orcid.org/0000-0002-0454-940X
Jinyang HuangSchool of Computer and Information, Hefei University of Technology, Hefei, China.ORCID http://orcid.org/0000-0001-5483-2812
Wenduo ChenSchool of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore.
Chao HanSchool of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore.
Hui MaSchool of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore.
Jianbo YuSchool of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore.
Zhenhan ZhangSchool of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore.
Chongwu WangSchool of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore.ORCID http://orcid.org/0000-0002-8749-196X
Qi Jie WangSchool of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore. qjwang@ntu.edu.sg.ORCID http://orcid.org/0000-0002-9910-1455

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multispectral features across visible (Vis), near-infrared (NIR) and mid-infrared (MIR) provide complementary information for intelligent vision in challenging environments. Precise extraction of multispectral features within the sensor level becomes increasingly critical, yet remains elusive for next-generation vision systems. Here we report a multispectral sensor constructed by a MoTe

Identifiers

PMID42816499
PMCPMC13627674

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.