Evidence map›Paper›PMID 39145254›Full record

ArticlePeerJ. Computer science2024

Adaptive adjacent context negotiation network for object detection in remote sensing imagery.

Yan Dong, Yundong Liu, Yuhua Cheng, Guangshuai Gao, Kai Chen, Chunlei Li

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ. Computer science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Yan DongSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Yundong LiuSchool of Electronic and Information Engineering, Zhongyuan University of Technology, ZhengZhou, China.
Yuhua ChengSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Guangshuai GaoSchool of Electronic and Information Engineering, Zhongyuan University of Technology, ZhengZhou, China.
Kai ChenSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Chunlei LiSchool of Electronic and Information Engineering, Zhongyuan University of Technology, ZhengZhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate localization of objects of interest in remote sensing images (RSIs) is of great significance for object identification, resource management, decision-making and disaster relief response. However, many difficulties, like complex backgrounds, dense target quantities, large-scale variations, and small-scale objects, which make the detection accuracy unsatisfactory. To improve the detection accuracy, we propose an Adaptive Adjacent Context Negotiation Network (A

Indexed as

Adjacent context negotiationGlobal to local aggregation enhancementObject detectionRemote sensing imagesSpectral context information

Identifiers

PMID39145254
PMCPMC11323134

What OpenQuestion holds

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LicenceCC BY-NC
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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.