Laser & Optoelectronics Progress, Volume. 59, Issue 10, 1010005(2022)
Fabric Defect Classification Algorithm Based on Multi-Scale Feature Fusion of Spatial Attention
[3] Jing J F, Chen S, Li P. Automatic defect detection of patterned fabric via combining the optimal Gabor filter and golden image subtraction[J]. Journal of Fiber Bioengineering and Informatics, 8, 229-239(2018).
[6] Li M, Cui S Q, Xie Z P. Application of Gaussian mixture model on defect detection of print fabric[J]. Journal of Textile Research, 36, 94-98(2015).
[10] Zhao Z Y, Ye L, Sang H S et al. Application of deep learning in fabric defect detection[J]. Foreign Electronic Measurement Technology, 38, 110-116(2019).
[11] Su Z B, Gao M, Li P F et al. Digital printing defect classification algorithm based on convolutional neural network[J]. Laser & Optoelectronics Progress, 57, 241011(2020).
[12] Zhou J, Jing J F, Zhang H H et al. Real-time fabric defect detection algorithm based on S-YOLOV3 model[J]. Laser & Optoelectronics Progress, 57, 161001(2020).
[18] Shi T T. Deep convolutional neural network fabric defect detection based on Fisher criterion[J]. Computer Systems & Applications, 28, 140-145(2019).
[19] Fu Y J, Zhang H L. Forest fire detection method based on transfer learning of convolutional neural network[J]. Laser & Optoelectronics Progress, 57, 041010(2020).
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Zhiyong Song, Haipeng Pan. Fabric Defect Classification Algorithm Based on Multi-Scale Feature Fusion of Spatial Attention[J]. Laser & Optoelectronics Progress, 2022, 59(10): 1010005
Category: Image Processing
Received: Apr. 14, 2021
Accepted: May. 18, 2021
Published Online: May. 16, 2022
The Author Email: Pan Haipeng (pan13989896598@163.com)