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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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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. |
format | Online Article Text |
id | pubmed-8913145 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT chenyongbin surfacedefectdetectionmethodbasedonimprovedattentionmechanismandfeaturefusionmodel AT wangguitang surfacedefectdetectionmethodbasedonimprovedattentionmechanismandfeaturefusionmodel AT fuqinshen surfacedefectdetectionmethodbasedonimprovedattentionmechanismandfeaturefusionmodel |