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Surface Defect Detection Method Based on Improved Attention Mechanism and Feature Fusion Model

Cylinder liners are important to automobile engines. The appearance quality will directly affect the life and safety of the engines. At present, the appearance quality inspection of cylinder liners mainly relies on manual visual judgment, which is easily affected by the subjective factors of inspect...

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Detalles Bibliográficos
Autores principales: Chen, Yongbin, Wang, Guitang, Fu, Qinshen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8913145/
https://www.ncbi.nlm.nih.gov/pubmed/35281189
http://dx.doi.org/10.1155/2022/3188645
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author Chen, Yongbin
Wang, Guitang
Fu, Qinshen
author_facet Chen, Yongbin
Wang, Guitang
Fu, Qinshen
author_sort Chen, Yongbin
collection PubMed
description Cylinder liners are important to automobile engines. The appearance quality will directly affect the life and safety of the engines. At present, the appearance quality inspection of cylinder liners mainly relies on manual visual judgment, which is easily affected by the subjective factors of inspectors. This paper studies improved machine vision to realize surface defect detection. It proposes the improvement of the attention mechanism and a feature fusion method to locate and classify the defect. Experiments show that the method proposed in this paper has improved both accuracy and speed, and it can detect defects in production and realize industrialization. At the same time, the method studied in this paper has the value of popularization and application for appearance defect detection in other fields.
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spelling pubmed-89131452022-03-11 Surface Defect Detection Method Based on Improved Attention Mechanism and Feature Fusion Model Chen, Yongbin Wang, Guitang Fu, Qinshen Comput Intell Neurosci Research Article Cylinder liners are important to automobile engines. The appearance quality will directly affect the life and safety of the engines. At present, the appearance quality inspection of cylinder liners mainly relies on manual visual judgment, which is easily affected by the subjective factors of inspectors. This paper studies improved machine vision to realize surface defect detection. It proposes the improvement of the attention mechanism and a feature fusion method to locate and classify the defect. Experiments show that the method proposed in this paper has improved both accuracy and speed, and it can detect defects in production and realize industrialization. At the same time, the method studied in this paper has the value of popularization and application for appearance defect detection in other fields. Hindawi 2022-03-03 /pmc/articles/PMC8913145/ /pubmed/35281189 http://dx.doi.org/10.1155/2022/3188645 Text en Copyright © 2022 Yongbin Chen et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Chen, Yongbin
Wang, Guitang
Fu, Qinshen
Surface Defect Detection Method Based on Improved Attention Mechanism and Feature Fusion Model
title Surface Defect Detection Method Based on Improved Attention Mechanism and Feature Fusion Model
title_full Surface Defect Detection Method Based on Improved Attention Mechanism and Feature Fusion Model
title_fullStr Surface Defect Detection Method Based on Improved Attention Mechanism and Feature Fusion Model
title_full_unstemmed Surface Defect Detection Method Based on Improved Attention Mechanism and Feature Fusion Model
title_short Surface Defect Detection Method Based on Improved Attention Mechanism and Feature Fusion Model
title_sort surface defect detection method based on improved attention mechanism and feature fusion model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8913145/
https://www.ncbi.nlm.nih.gov/pubmed/35281189
http://dx.doi.org/10.1155/2022/3188645
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AT wangguitang surfacedefectdetectionmethodbasedonimprovedattentionmechanismandfeaturefusionmodel
AT fuqinshen surfacedefectdetectionmethodbasedonimprovedattentionmechanismandfeaturefusionmodel