计算机应用与软件2025，Vol.42Issue(5)：146-154,9.DOI:10.3969/j.issn.1000-386x.2025.05.021
风格迁移增强的机场目标检测方法研究
STYLE TRANSFER INSPIRED AIRPORT OBJECT DETECTION
摘要
Abstract
In image-based object detection,the airport is an important kind of object,and automatic recognition of it is of great significance.Aimed at the difficulty of general detection algorithms to correctly extract edge information from complex aerial images,a new object detection algorithm based on style transfer is proposed to enhanced edge feature extraction.The image noise was suppressed by using the generative adversarial network.The noise-suppressed image was transported to an edge detection algorithm to highlight the edge features.The highlighted images were used to complete the airport location detection through the object detection algorithm.In the airport object detection experiment,the object detection algorithm combined with the edge feature extraction approach proposed in this paper has higher precision than the original object detection algorithm.The average precision of YOLOv5 and the proposed feature extraction fusion algorithm achieves 97.7％.Experimental results demonstrate that this feature extraction approach has a good effect on airport object detection.关键词
风格迁移/生成对抗网络/目标检测/机场检测/边缘增强Key words
Style transfer/Generative adversarial network/Object detection/Airport detection/Edge enhancement分类
计算机与自动化引用本文复制引用
王欣,李屹,孟天宇,黄佳琪..风格迁移增强的机场目标检测方法研究[J].计算机应用与软件,2025,42(5):146-154,9.基金项目
国家自然科学基金民航联合基金重点项目(U2033213) （U2033213）
中国民用航空飞行学院面上项目(J2019-045). （J2019-045）
