Research on surface defect intelligent detection technology of non-woven fabric based on support vector machine
Author:
Affiliation:
1. Electromechanic Engineering Institute, Foshan Polytechnic,Foshan,Guangdong,China,528137
Funder
Characteristic innovation project of colleges and universities in Guangdong Province in 2019
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9744727/9744728/09744952.pdf?arnumber=9744952
Reference8 articles.
1. The obtainment and recognition of raw silk defects based on machine vision and image analysis
2. Differential evolution-based optimal Gabor filter model for fabric inspection
3. Deep-Learning-Based Small Surface Defect Detection via an Exaggerated Local Variation-Based Generative Adversarial Network
4. A study on the recognition and classification of embroidered textile defects in manufacturing
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2. Intelligent Quality Control of Surface Defects in Fabrics: A Comprehensive Research Progress;IEEE Access;2024
3. Garment Defect Detection Using Convolutional Neural Network;2023 5th International Conference on Advancements in Computing (ICAC);2023-12-07
4. Analyzing the Effectiveness of Various ML and DL Models in Detecting Defects in Textile Fabrics;2023 International Conference on Sustainable Communication Networks and Application (ICSCNA);2023-11-15
5. Using DLT for Textile Fabric Inspection: A Novel Network for Detecting Fabric Defects;2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN);2023-05-05
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