Evidence map›Paper›PMID 40285288›Full record

ArticleSensors (Basel, Switzerland)2025

A New Algorithm for Visual Navigation in Unmanned Aerial Vehicle Water Surface Inspection.

Jianfeng Han, Xiongwei Gao, Lili Song, Jiandong Fang, Yongzhao Tao, Haixin Deng, Jie Yao

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. 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

7 authors.

Jianfeng HanSchool of Information Engineering, Inner Mongolia University of Technology, Hohhot 010080, China.
Xiongwei GaoSchool of Information Engineering, Inner Mongolia University of Technology, Hohhot 010080, China.
Lili SongSchool of Information Engineering, Inner Mongolia University of Technology, Hohhot 010080, China.
Jiandong FangSchool of Information Engineering, Inner Mongolia University of Technology, Hohhot 010080, China.ORCID 0000-0002-2920-9276
Yongzhao TaoSchool of Information Engineering, Inner Mongolia University of Technology, Hohhot 010080, China.ORCID 0009-0001-0388-9293
Haixin DengSchool of Information Engineering, Inner Mongolia University of Technology, Hohhot 010080, China.
Jie YaoSchool of Information Engineering, Inner Mongolia University of Technology, Hohhot 010080, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Water surface inspection is a crucial instrument for safeguarding the aquatic environment. UAVs enhance the efficiency of water area inspections due to their high mobility and extensive coverage. This paper introduces two UAV inspection methodologies for the characteristics of rivers and lakes, along with an efficient semantic segmentation algorithm, WaterSegLite (Water Segmentation Lightweight algorithm), for UAV visual navigation. The algorithm employs the UAV's aerial perspective alongside a streamlined neural network architecture to facilitate rapid real-time segmentation of water bodies and to furnish positional data to the UAV for visual navigation. The experimental findings indicate that WaterSegLite achieves a segmentation accuracy (mIoU) of 93.81% and an F1 score of 95.44%, surpassing the baseline model by 2.7% and 2.23%, respectively. Simultaneously, the processing frame rate of this algorithm on the airborne device attains 28.27 frames per second, fully satisfying the requirements for real-time water surface inspection by UAVs. This paper offers technical assistance for UAV inspection techniques in aquatic environments and presents innovative concepts for the intelligent advancement of water surface inspection.

Indexed as

attention mechanismriver trackingsemantic segmentationUAVvisual navigation

Identifiers

PMID40285288
PMCPMC12030802

What OpenQuestion holds

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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.