QA

Yifang Tan, Lijun Yuan, Chuanjiang Xie, Chao Zhou, Xin Li, Xinyu Zhu

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 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

6 authors.

Yifang TanCollege of Aviation Electronics and Electrical Engineering, Civil Aviation Flight University of China, Guanghan 618307, China.

Lijun YuanCollege of Aviation Electronics and Electrical Engineering, Civil Aviation Flight University of China, Guanghan 618307, China.ORCID 0009-0000-2527-3716

Chuanjiang XieCollege of Aviation Electronics and Electrical Engineering, Civil Aviation Flight University of China, Guanghan 618307, China.

Chao ZhouCollege of Aviation Electronics and Electrical Engineering, Civil Aviation Flight University of China, Guanghan 618307, China.

Xin LiCollege of Aviation Electronics and Electrical Engineering, Civil Aviation Flight University of China, Guanghan 618307, China.ORCID 0000-0002-7368-6248

Xinyu ZhuCollege of Aviation Electronics and Electrical Engineering, Civil Aviation Flight University of China, Guanghan 618307, China.

Funding

Civil Aviation Flight University of China 202510624019,25CAFUC10022Document from Sichuan Engineering Research Center for Intelligent Operation and Maintenance of Civil Aviation Airports JCZX2024ZZ24Education Talent Program of Civil Aviation Administration of China MHJY2025009

6 · The paper itself

Abstract

Visible-thermal tiny pedestrian detection in UAV aerial images is crucial for online decision-making in urban security and disaster response. However, the extremely small scale and sparse distribution of pedestrians cause discriminative cues to be submerged by dominant low-frequency background and contextual redundancy during feature learning. Meanwhile, cross-modal spatial misalignment and spatially varying modality reliability hinder stable fine-grained correspondence, thereby degrading fusion quality. To address these issues, QA

Indexed as

aerial imagesfeature alignmentquality priorRGBT fusiontiny person detection

Identifiers

PMID42280959

DOI10.3390/s26113443

PMCPMC13258944

What OpenQuestion 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 OpenQuestion graph.