Welding defect detection with image processing on a custom small dataset: A comparative study
Abstract This work focuses on detecting defects in welding seams using the most advanced You Only Look Once (YOLO) algorithms and transfer learning. To this end, the authors prepared a small dataset of images using manual welding and compared the performance of the YOLO v5, v6, v7, and v8 methods af...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-12-01
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| Series: | IET Collaborative Intelligent Manufacturing |
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| Online Access: | https://doi.org/10.1049/cim2.70005 |
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| author | József Szőlősi Béla J. Szekeres Péter Magyar Bán Adrián Gábor Farkas Mátyás Andó |
| author_facet | József Szőlősi Béla J. Szekeres Péter Magyar Bán Adrián Gábor Farkas Mátyás Andó |
| author_sort | József Szőlősi |
| collection | DOAJ |
| description | Abstract This work focuses on detecting defects in welding seams using the most advanced You Only Look Once (YOLO) algorithms and transfer learning. To this end, the authors prepared a small dataset of images using manual welding and compared the performance of the YOLO v5, v6, v7, and v8 methods after two‐step training. Key findings reveal that YOLOv7 demonstrates superior performance, suggesting its potential as a valuable tool in automated welding quality control. The authors’ research underscores the importance of model selection. It lays the groundwork for future exploration in larger datasets and varied welding scenarios, potentially contributing to defect detection practices in manufacturing industries. The dataset and the code repository links are also provided to support our findings. |
| format | Article |
| id | doaj-art-4e2b940b491b4bbc8a521e3810ccac91 |
| institution | DOAJ |
| issn | 2516-8398 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Collaborative Intelligent Manufacturing |
| spelling | doaj-art-4e2b940b491b4bbc8a521e3810ccac912025-08-20T02:43:50ZengWileyIET Collaborative Intelligent Manufacturing2516-83982024-12-0164n/an/a10.1049/cim2.70005Welding defect detection with image processing on a custom small dataset: A comparative studyJózsef Szőlősi0Béla J. Szekeres1Péter Magyar2Bán Adrián3Gábor Farkas4Mátyás Andó5ELTE Eötvös Loránd University Doctoral School of Informatics Budapest HungaryDepartment of Numerical Analysis ELTE Eötvös Loránd University Faculty of Informatics Budapest HungaryELTE Eötvös Loránd University Doctoral School of Informatics Budapest HungaryELTE Eötvös Loránd University Faculty of Informatics Szombathely HungaryDepartment of Computer Algebra ELTE Eötvös Loránd University Faculty of Informatics Budapest HungaryELTE Eötvös Loránd University Faculty of Informatics Institute of Computer Science Budapest HungaryAbstract This work focuses on detecting defects in welding seams using the most advanced You Only Look Once (YOLO) algorithms and transfer learning. To this end, the authors prepared a small dataset of images using manual welding and compared the performance of the YOLO v5, v6, v7, and v8 methods after two‐step training. Key findings reveal that YOLOv7 demonstrates superior performance, suggesting its potential as a valuable tool in automated welding quality control. The authors’ research underscores the importance of model selection. It lays the groundwork for future exploration in larger datasets and varied welding scenarios, potentially contributing to defect detection practices in manufacturing industries. The dataset and the code repository links are also provided to support our findings.https://doi.org/10.1049/cim2.70005data analysisdecision makingintelligent manufacturing systemslearning (artificial intelligence)manufacturing systemsneural nets |
| spellingShingle | József Szőlősi Béla J. Szekeres Péter Magyar Bán Adrián Gábor Farkas Mátyás Andó Welding defect detection with image processing on a custom small dataset: A comparative study IET Collaborative Intelligent Manufacturing data analysis decision making intelligent manufacturing systems learning (artificial intelligence) manufacturing systems neural nets |
| title | Welding defect detection with image processing on a custom small dataset: A comparative study |
| title_full | Welding defect detection with image processing on a custom small dataset: A comparative study |
| title_fullStr | Welding defect detection with image processing on a custom small dataset: A comparative study |
| title_full_unstemmed | Welding defect detection with image processing on a custom small dataset: A comparative study |
| title_short | Welding defect detection with image processing on a custom small dataset: A comparative study |
| title_sort | welding defect detection with image processing on a custom small dataset a comparative study |
| topic | data analysis decision making intelligent manufacturing systems learning (artificial intelligence) manufacturing systems neural nets |
| url | https://doi.org/10.1049/cim2.70005 |
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