单发
计算机科学
目标检测
探测器
块(置换群论)
人工智能
模式识别(心理学)
算法
数学
光学
电信
几何学
物理
作者
Huosheng Xie,Yafeng Zhang,Zesen Wu
出处
期刊:AATCC journal of research
[American Association of Textile Chemists and Colorists - AATCC]
日期:2021-09-01
卷期号:8 (1_suppl): 181-190
被引量:14
摘要
The fabric defect detection algorithm based on object detection has become a research hotspot. The method based on the Single Shot MultiBox Detector (SSD) model has a fast detection speed, but the detection accuracy is insufficient. To balance the detection speed and accuracy of the model and meet the actual needs of the industry, an improved fabric defect detection algorithm based on SSD is proposed in this study. The Fully Convolutional Squeeze-and-Excitation (FCSE) block is added into the traditional SSD to improve the detection accuracy of the model. The number of default boxes was adjusted to accommodate the detection of long strip defects on fabric surface. Experimental results on the TILDA and Xuelang dataset confirm that our detection method based on SSD efficiently detected various fabric defects.
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