基于YOLOv5s的车辆漆面缺陷检测方法
Vehicle Paint Defect Detection Method Based on YOLOv5s
郝友胜 1白鑫 1文贞慧1
作者信息
- 1. 广西大学电气工程学院,广西南宁 530000
- 折叠
摘要
提出了一种基于YOLOv5s的车辆漆面检测方法,以提高检测效率和准确性.为了适应车辆漆面检测任务,构建了一个大规模的车辆漆面数据集,并对其进行了详细标注和预处理.结果表明,基于YOLOv5s的车辆漆面检测方法在准确性和效率方面表现出色,能快速且精确地识别车辆漆面上的缺陷,为汽车制造商和维修工厂提供一种高效的质量控制工具.
Abstract
This study aims to propose a vehicle paint detection method based on YOLOv5s to improve detection efficiency and accuracy.In order to adapt to the task of vehicle paint detection,a large-scale data set of vehicle paint is constructed,and it is marked and preprocessed in detail.The results show that the vehicle paint detection method based on YOLOv5s performs well in terms of accuracy and efficiency,and can quickly and accurately identify defects in vehicle paint,providing an efficient quality control tool for automobile manufacturers and maintenance factories.
关键词
漆面检测/数据集/深度学习/YOLOv5s算法Key words
paint detection/data set/deep learning/YOLOv5s algorithm引用本文复制引用
出版年
2024
NETL
NSTL
万方数据