棉纺织技术2023，Vol.51Issue(12)：20-25,6.
基于YOLOv5-Eff网络的织物疵点检测算法
Fabric defect detection algorithm based on YOLOv5-Eff network
石玉文 1林富生 1宋志峰 1余联庆1
作者信息
- 1. 武汉纺织大学,湖北武汉,430200||三维纺织湖北省工程研究中心,湖北武汉,430200||湖北省数字化纺织装备重点实验室,湖北武汉,430200
- 折叠
摘要
Abstract
Aiming at the problems of low target detection precision,miss detectioning easily for small targets and so on,a detection algorithm based on improved YOLOv5 model was proposed.The improved EfficientNet-B1 network was selected as the backbone feature extraction network.The attention module of ACMIX was introduced to improve the sensitivity of the network to small-scale targets,reduce the impact of noise and solve the distortion condition of small defect characteristic pattern during convolution operation.SiLU and Swish activation function were combined.Dynamic threshold value was adjusted and flexibility of the algorithm was improved according to the target quantity and density.The results showed that the precision,recall and mAP value of improved YOLOv5 algorithm were improved by 4.33 percentage points,2.11 percentage points and 4.32 percentage points respectively compared with the original YOLOv5 model.The algorithm could accurately identify the overall characteristics of fabric defects,and was more suitable for the detection of defects in complex scenes and small targets.关键词
YOLOv5/EfficientNet/注意力模块/Swish动态激活函数/织物疵点Key words
YOLOv5/EfficientNet/attention module/Swish dynamic activation function/fabric defect分类
计算机与自动化引用本文复制引用
石玉文,林富生,宋志峰,余联庆..基于YOLOv5-Eff网络的织物疵点检测算法[J].棉纺织技术,2023,51(12):20-25,6.
