Research on Fabric Defect Detection Algorithm Based on Lightweight YOLOv7-Tiny

Research on Fabric Defect Detection Algorithm Based on Lightweight YOLOv7-Tiny

The current advanced neural network models are expanding in size and complexity to achieve improved detection accuracy. This study designs a lightweight fabric defect detection algorithm based on YOLOv7-tiny, called YOLOv7-tiny-MGCK. Its objectives are to improve the performance of fabric defect det...

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Bibliographic Details
Main Authors: Tang Li, Mei Shunqi, Shi Yishan, Zhou Shi, Zheng Quan, Hongkai Jiang, Xu Qiao, Zhang Zhiming
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Journal of Natural Fibers
Subjects:
Neural network
fabric defect detection
activation function
Ghost module
upsampling
clustering algorithm
Online Access:https://www.tandfonline.com/doi/10.1080/15440478.2024.2352753
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https://www.tandfonline.com/doi/10.1080/15440478.2024.2352753

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