Evidence map›Paper›PMID 37960370›Full record

ArticleSensors (Basel, Switzerland)2023

A Rust Extraction and Evaluation Method for Navigation Buoys Based on Improved U-Net and Hue, Saturation, and Value.

Shunan Hu, Haiyan Duan, Jiansen Zhao, Hailiang Zhao

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. 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

4 authors.

Shunan HuSchool of Automotive Engineering, Changshu Institute of Technology, Changshu 215506, China.ORCID 0009-0008-3479-1724
Haiyan DuanMerchant Marine College, Shanghai Maritime University, Shanghai 201306, China.
Jiansen ZhaoMerchant Marine College, Shanghai Maritime University, Shanghai 201306, China.ORCID 0000-0002-2065-9481
Hailiang ZhaoMerchant Marine College, Shanghai Maritime University, Shanghai 201306, China.ORCID 0009-0005-0146-9809

Funding

National Key Research and Development Program, China 2021YFC2801004National Natural Science Foundation of China 51709167Shanghai Science and Technology Innovation Action Plan 21DZ1205803Shanghai Science and Technology Innovation Action Plan 22DZ1204503
6 · The paper itself

Abstract

Abnormalities of navigation buoys include tilting, rusting, breaking, etc. Realizing automatic extraction and evaluation of rust on buoys is of great significance for maritime supervision. Severe rust may cause damage to the buoy itself. Therefore, a lightweight method based on machine vision is proposed for extracting and evaluating the rust of the buoy. The method integrates image segmentation and processing. Firstly, image segmentation technology is used to extract the metal part of the buoy based on an improved U-Net. Secondly, the RGB image is converted into an HSV image by preprocessing, and the transformation law of HSV channel color value is analyzed to obtain the best segmentation threshold and then the pixels of the rusted and the metal parts can be extracted. Finally, the rust ratio of the buoy is calculated to evaluate the rust level of the buoy. Results show that both the segmentation precision and recall are above 0.95, and the accuracy is nearly 1.00. Compared with the rust evaluation algorithm directly using the image processing method, the accuracy and processing speed of rust grade evaluation are greatly improved.

Indexed as

HSVimproved U-Net methodnavigation buoyrust extraction

Identifiers

PMID37960370
PMCPMC10648957

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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.