Evidence map›Paper›PMID 41948303›Full record

ArticleFrontiers in plant science2026

ACG-Net: an attention context-guided network for fine segmentation of

Yuxin Zhang, Huajuan Gao, Tingting Leng, Xiang Liu, Di Zhang, Zhijie Li, Peng Zhu

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

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0citing papers in PubMed
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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

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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

7 authors.

Yuxin ZhangCollege of Information Engineering, Sichuan Agricultural University, Ya'an, China.
Huajuan GaoCollege of Information Engineering, Sichuan Agricultural University, Ya'an, China.
Tingting LengCollege of Information Engineering, Sichuan Agricultural University, Ya'an, China.
Xiang LiuCollege of Information Engineering, Sichuan Agricultural University, Ya'an, China.
Di ZhangFaculty of Public Administration, Sichuan Agricultural University, Ya'an, China.
Zhijie LiKey Laboratory of Ecological Forestry Engineering of Sichuan Province, College of Forestry, Sichuan Agricultural University, Chengdu, China.
Peng ZhuKey Laboratory of Ecological Forestry Engineering of Sichuan Province, College of Forestry, Sichuan Agricultural University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The genus Methods: To address these challenges, we constructed a high-resolution UAV image segmentation dataset for Results: Experimental results demonstrate that ES-REF improves model robustness, increasing the mIoU of U-Net and ACG-Net by 0.71 and 2.18 percentage points, respectively. On the test set, ACG-Net achieved an mIoU of 89.55%, outperforming the U-Net baseline by 4.31 percentage points and surpassing models such as DeepLabv3+. Discussion: This work establishes a data and methodological foundation for automated

Indexed as

data augmentationFagusforest resource monitoringremote sensingsemantic segmentationsmart forestryUAV image segmentation

Identifiers

PMID41948303
PMCPMC13051272

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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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.