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This study presents an improved fabric defect detection method based on SSD. This method uses a powerful CNN to extract defect features and introduces a channel attention mechanism FCSE block to enhance the weight of defective areas in each channel of the feature map.
Mar 28, 2022
Oct 6, 2018 · In this paper, Fabric defect detection is a challenging task because of the complex texture. Deep learning technology provide a promising ...
ABSTRACT. In this paper, Fabric defect detection is a challenging task because of the complex texture. Deep learning technology provide a.
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Experimental results showed that the improved SSD model can accurately detect the defect region and the original SSD model may fail to detect the small ...
Nov 10, 2022 · Large-scale feature maps can be used to detect small defects in fabrics, and small-scale feature maps can be used to detect larger ones, this is ...
In this paper, Fabric defect detection is a challenging task because of the complex texture. Deep learning technology provide a promising solution.
Mar 6, 2024 · Experimental results show that the proposed algorithm is superior to SSD, Faster_RCNN, Yolo_v4 tiny and Yolo_v4 algorithms in fabric defect ...
Sep 30, 2022 · Fabric defect detection is the important step of ensuring the quality and price of textiles. In order to make the automatic fabric defect ...
In this paper, the proposed YOLOv8n-LAW fabric defect detection algorithm, when compared to the first-stage detection algorithm SSD, shows a 57.2% increase in ...
Nov 5, 2022 · To effectively detect small defects and defects in colored fabrics, Zhao and Zhang [112] proposed an adaptive multiscale fabric defect detection ...