Optimization and Validation of Wafer Surface Defect Detection Algorithm Based on RT-DETR
In response to the issue of poor detection performance on wafer surface defect spots and elongated scratches, an improved RT-DETR method for wafer surface defect detection is proposed. Firstly, a dynamic snake convolutional layer is introduced to detect elongated scratches where conventional convolu...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10892113/ |
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| _version_ | 1850033681102536704 |
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| author | Ao Xu Yanwei Li Hongbo Xie Rui Yang Jianjie Li Jiaying Wang |
| author_facet | Ao Xu Yanwei Li Hongbo Xie Rui Yang Jianjie Li Jiaying Wang |
| author_sort | Ao Xu |
| collection | DOAJ |
| description | In response to the issue of poor detection performance on wafer surface defect spots and elongated scratches, an improved RT-DETR method for wafer surface defect detection is proposed. Firstly, a dynamic snake convolutional layer is introduced to detect elongated scratches where conventional convolutional kernels fail to extract features effectively. Secondly, to address the problem of information loss in small targets, an attention-based Transformer encoder module and a feature fusion network based on residual thinking are proposed. Finally, verification is conducted using a wafer test dataset. Experimental results demonstrate that compared to the original RT-DETR method, the model exhibits a 4.1% improvement in detecting small particles and a 5.4% improvement in scratch detection performance. Fully meeting the requirements of intelligent manufacturing and high detection accuracy. |
| format | Article |
| id | doaj-art-75607637eb0c44c7aa63ac04a4ec73fe |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-75607637eb0c44c7aa63ac04a4ec73fe2025-08-20T02:58:07ZengIEEEIEEE Access2169-35362025-01-0113397273973710.1109/ACCESS.2025.354352510892113Optimization and Validation of Wafer Surface Defect Detection Algorithm Based on RT-DETRAo Xu0https://orcid.org/0009-0009-4524-5427Yanwei Li1https://orcid.org/0009-0004-7402-3640Hongbo Xie2https://orcid.org/0000-0003-2116-973XRui Yang3https://orcid.org/0000-0003-3738-1612Jianjie Li4https://orcid.org/0000-0002-8838-4621Jiaying Wang5https://orcid.org/0000-0002-2174-2009Northeastern University, Shenyang, ChinaJi Hua Laboratory, Foshan, ChinaJi Hua Laboratory, Foshan, ChinaJi Hua Laboratory, Foshan, ChinaJi Hua Laboratory, Foshan, ChinaJi Hua Laboratory, Foshan, ChinaIn response to the issue of poor detection performance on wafer surface defect spots and elongated scratches, an improved RT-DETR method for wafer surface defect detection is proposed. Firstly, a dynamic snake convolutional layer is introduced to detect elongated scratches where conventional convolutional kernels fail to extract features effectively. Secondly, to address the problem of information loss in small targets, an attention-based Transformer encoder module and a feature fusion network based on residual thinking are proposed. Finally, verification is conducted using a wafer test dataset. Experimental results demonstrate that compared to the original RT-DETR method, the model exhibits a 4.1% improvement in detecting small particles and a 5.4% improvement in scratch detection performance. Fully meeting the requirements of intelligent manufacturing and high detection accuracy.https://ieeexplore.ieee.org/document/10892113/Defects detectiondeep learningobject detection |
| spellingShingle | Ao Xu Yanwei Li Hongbo Xie Rui Yang Jianjie Li Jiaying Wang Optimization and Validation of Wafer Surface Defect Detection Algorithm Based on RT-DETR IEEE Access Defects detection deep learning object detection |
| title | Optimization and Validation of Wafer Surface Defect Detection Algorithm Based on RT-DETR |
| title_full | Optimization and Validation of Wafer Surface Defect Detection Algorithm Based on RT-DETR |
| title_fullStr | Optimization and Validation of Wafer Surface Defect Detection Algorithm Based on RT-DETR |
| title_full_unstemmed | Optimization and Validation of Wafer Surface Defect Detection Algorithm Based on RT-DETR |
| title_short | Optimization and Validation of Wafer Surface Defect Detection Algorithm Based on RT-DETR |
| title_sort | optimization and validation of wafer surface defect detection algorithm based on rt detr |
| topic | Defects detection deep learning object detection |
| url | https://ieeexplore.ieee.org/document/10892113/ |
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