Intelligent Detection Method of Aircraft Skin Damage
This paper proposes an aircraft skin damage detection network based on YOLO v5.It utilizes StyleGAN to generate synthetic images for training the proposed aircraft skin defect detection network.Through the proposed StyleGAN-based YOLO v5 model,the capabilities of detecting small targets,capturing low-sensitivity spatial information,and performing global optimization are enhanced.The model developed in this paper has been trained,validated,and tested using field-captured and synthesized skin damage photos.The proposed detection model achieves an accuracy rate of 92.2％and a recall rate of 92.3％,which are 10.7％and 12.5％higher than the original YOLO v5,respectively.The StyleGAN-based YOLO v5 exhibits high precision and robustness,and this model can significantly improve the efficiency of aircraft skin damage detection and reduce the misjudgment rate.
万方数据
维普
