Flaw Detection in White Porcelain Wine Bottles Based on Improved YOLOv4 Algorithm
Aiming at the problems of low detection accuracy and slow detection speed in white porcelain wine bottle flaw detection, an improved flaw detection algorithm based on YOLOv4 was proposed. By adding Coordinate Attention to the backbone feature extraction network, the extracting ability of white porce...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-07-01
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| Series: | Frontiers in Bioengineering and Biotechnology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fbioe.2022.928900/full |
| _version_ | 1811219245823950848 |
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| author | Guoqiang Gong Jun Huang Hemin Wang |
| author_facet | Guoqiang Gong Jun Huang Hemin Wang |
| author_sort | Guoqiang Gong |
| collection | DOAJ |
| description | Aiming at the problems of low detection accuracy and slow detection speed in white porcelain wine bottle flaw detection, an improved flaw detection algorithm based on YOLOv4 was proposed. By adding Coordinate Attention to the backbone feature extraction network, the extracting ability of white porcelain bottle flaw features was improved. Deformable convolution is added to locate flaws more accurately, so as to improve the detection accuracy of flaws by the model. Efficient Intersection over Union was used to replace Complete Intersection over Union in YOLOv4 to improve the loss function and improve the model detection speed and accuracy. Experimental results on the surface flaw data set of white porcelain wine bottles show that the proposed algorithm can effectively detect white porcelain wine bottle flaws, the mean Average Precision of the model can reach 92.56%, and the detection speed can reach 37.17 frames/s. |
| first_indexed | 2024-04-12T07:22:58Z |
| format | Article |
| id | doaj.art-a84d4b4ee62546338032e178d0e25bec |
| institution | Directory Open Access Journal |
| issn | 2296-4185 |
| language | English |
| last_indexed | 2024-04-12T07:22:58Z |
| publishDate | 2022-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioengineering and Biotechnology |
| spelling | doaj.art-a84d4b4ee62546338032e178d0e25bec2022-12-22T03:42:16ZengFrontiers Media S.A.Frontiers in Bioengineering and Biotechnology2296-41852022-07-011010.3389/fbioe.2022.928900928900Flaw Detection in White Porcelain Wine Bottles Based on Improved YOLOv4 AlgorithmGuoqiang GongJun HuangHemin WangAiming at the problems of low detection accuracy and slow detection speed in white porcelain wine bottle flaw detection, an improved flaw detection algorithm based on YOLOv4 was proposed. By adding Coordinate Attention to the backbone feature extraction network, the extracting ability of white porcelain bottle flaw features was improved. Deformable convolution is added to locate flaws more accurately, so as to improve the detection accuracy of flaws by the model. Efficient Intersection over Union was used to replace Complete Intersection over Union in YOLOv4 to improve the loss function and improve the model detection speed and accuracy. Experimental results on the surface flaw data set of white porcelain wine bottles show that the proposed algorithm can effectively detect white porcelain wine bottle flaws, the mean Average Precision of the model can reach 92.56%, and the detection speed can reach 37.17 frames/s.https://www.frontiersin.org/articles/10.3389/fbioe.2022.928900/fullflaw detectionwhite porcelain bottleYOLOv4CA mechanismdeformable convolutionloss function |
| spellingShingle | Guoqiang Gong Jun Huang Hemin Wang Flaw Detection in White Porcelain Wine Bottles Based on Improved YOLOv4 Algorithm Frontiers in Bioengineering and Biotechnology flaw detection white porcelain bottle YOLOv4 CA mechanism deformable convolution loss function |
| title | Flaw Detection in White Porcelain Wine Bottles Based on Improved YOLOv4 Algorithm |
| title_full | Flaw Detection in White Porcelain Wine Bottles Based on Improved YOLOv4 Algorithm |
| title_fullStr | Flaw Detection in White Porcelain Wine Bottles Based on Improved YOLOv4 Algorithm |
| title_full_unstemmed | Flaw Detection in White Porcelain Wine Bottles Based on Improved YOLOv4 Algorithm |
| title_short | Flaw Detection in White Porcelain Wine Bottles Based on Improved YOLOv4 Algorithm |
| title_sort | flaw detection in white porcelain wine bottles based on improved yolov4 algorithm |
| topic | flaw detection white porcelain bottle YOLOv4 CA mechanism deformable convolution loss function |
| url | https://www.frontiersin.org/articles/10.3389/fbioe.2022.928900/full |
| work_keys_str_mv | AT guoqianggong flawdetectioninwhiteporcelainwinebottlesbasedonimprovedyolov4algorithm AT junhuang flawdetectioninwhiteporcelainwinebottlesbasedonimprovedyolov4algorithm AT heminwang flawdetectioninwhiteporcelainwinebottlesbasedonimprovedyolov4algorithm |