A Suggestion System According to Fabric Control Time
Author:
Publisher
Gazi University Journal of Science
Subject
Multidisciplinary,General Engineering
Reference24 articles.
1. Shi, M., Jiang, S., Wang, H., Xu, B. “A simplified pulse-coupled neural network for adaptive segmentation of fabric defects”, Machine Vision and Applications , 20(2): 131-138, (2009).
2. Kaynar, O., Işik, Y. E., Görmez, Y., Demirkoparan, F. “Fabric defect detection with LBP-GLMC”, International Artificial Intelligence and Data Processing Symposium (IDAP), 1-5, (2017).
3. Zhang, L., Jing, J., Zhang, H., “Fabric defect classification based on LBP and GLCM”, Journal of Fiber Bioengineering and Informatics, 8(1): 81-89, (2015).
4. Huang, C. C., Chen, I. C., “Neural-fuzzy classification for fabric defects”, Textile Research Journal, 71(3): 220-224, (2001).
5. Beljadid, A., Tannouche, A., Balouki, A., “Application of deep learning for the detection of default in fabric texture”, 6th International Conference on Optimization and Applications (ICOA), pp. 1-5, (2020).
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1. Determination of various fabric defects using different machine learning techniques;The Journal of The Textile Institute;2023-05-02
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