GEB-YOLO: Optimized YOLOv7 Model for Surface Defect Detection on Aluminum Profiles
In recent years, achieving high-precision and high-speed target detection of surface defects on aluminum profiles to meet the requirements of industrial applications has been challenging. In this paper, the GEB-YOLO is proposed based on the YOLOv7 algorithm. First, the global attention mechanism (GA...
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MDPI AG
2024-09-01
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| Series: | Engineering Proceedings |
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| author | Zihao Xu Jinran Hu Xingyi Xiao Yujian Xu |
| author_facet | Zihao Xu Jinran Hu Xingyi Xiao Yujian Xu |
| author_sort | Zihao Xu |
| collection | DOAJ |
| description | In recent years, achieving high-precision and high-speed target detection of surface defects on aluminum profiles to meet the requirements of industrial applications has been challenging. In this paper, the GEB-YOLO is proposed based on the YOLOv7 algorithm. First, the global attention mechanism (GAM) is introduced, highlighting defect features. Second, the Explicit Visual Center Block (EVCBlock) is integrated into the network for key information extraction. Meanwhile, the BiFPN network structure is adopted to enhance feature fusion. The ablation experiments have demonstrated that the defect detection accuracy of the GEB-YOLO model is improved by 6.3%, and the speed is increased by 15% compared to the YOLOv7 model. |
| format | Article |
| id | doaj-art-e0f89c3e24224296adf752aaf98494bd |
| institution | DOAJ |
| issn | 2673-4591 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj-art-e0f89c3e24224296adf752aaf98494bd2025-08-20T02:42:38ZengMDPI AGEngineering Proceedings2673-45912024-09-017512810.3390/engproc2024075028GEB-YOLO: Optimized YOLOv7 Model for Surface Defect Detection on Aluminum ProfilesZihao Xu0Jinran Hu1Xingyi Xiao2Yujian Xu3College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, ChinaCollege of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, ChinaCollege of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, ChinaCollege of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, ChinaIn recent years, achieving high-precision and high-speed target detection of surface defects on aluminum profiles to meet the requirements of industrial applications has been challenging. In this paper, the GEB-YOLO is proposed based on the YOLOv7 algorithm. First, the global attention mechanism (GAM) is introduced, highlighting defect features. Second, the Explicit Visual Center Block (EVCBlock) is integrated into the network for key information extraction. Meanwhile, the BiFPN network structure is adopted to enhance feature fusion. The ablation experiments have demonstrated that the defect detection accuracy of the GEB-YOLO model is improved by 6.3%, and the speed is increased by 15% compared to the YOLOv7 model.https://www.mdpi.com/2673-4591/75/1/28target detectionsurface defectsGEB-YOLOattention mechanismBiFPN |
| spellingShingle | Zihao Xu Jinran Hu Xingyi Xiao Yujian Xu GEB-YOLO: Optimized YOLOv7 Model for Surface Defect Detection on Aluminum Profiles Engineering Proceedings target detection surface defects GEB-YOLO attention mechanism BiFPN |
| title | GEB-YOLO: Optimized YOLOv7 Model for Surface Defect Detection on Aluminum Profiles |
| title_full | GEB-YOLO: Optimized YOLOv7 Model for Surface Defect Detection on Aluminum Profiles |
| title_fullStr | GEB-YOLO: Optimized YOLOv7 Model for Surface Defect Detection on Aluminum Profiles |
| title_full_unstemmed | GEB-YOLO: Optimized YOLOv7 Model for Surface Defect Detection on Aluminum Profiles |
| title_short | GEB-YOLO: Optimized YOLOv7 Model for Surface Defect Detection on Aluminum Profiles |
| title_sort | geb yolo optimized yolov7 model for surface defect detection on aluminum profiles |
| topic | target detection surface defects GEB-YOLO attention mechanism BiFPN |
| url | https://www.mdpi.com/2673-4591/75/1/28 |
| work_keys_str_mv | AT zihaoxu gebyolooptimizedyolov7modelforsurfacedefectdetectiononaluminumprofiles AT jinranhu gebyolooptimizedyolov7modelforsurfacedefectdetectiononaluminumprofiles AT xingyixiao gebyolooptimizedyolov7modelforsurfacedefectdetectiononaluminumprofiles AT yujianxu gebyolooptimizedyolov7modelforsurfacedefectdetectiononaluminumprofiles |