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What is Improved YOLOv5 for Fabric Defect Detection about?

The article presents an improved YOLOv5 algorithm for automatic fabric defect detection, addressing inefficiencies of traditional manual methods. It employs a teacher-student architecture to enhance performance despite limited defect images, utilizing multitask learning and attention mechanisms for better recognition of both common and specific defects. Evaluations on public datasets demonstrate the method

Author

ivanapg96

Language

EN