上海航天（中英文）2024，Vol.41Issue(3)：121-129,9.DOI:10.19328/j.cnki.2096-8655.2024.03.013
多域特征引导的无监督SAR图像舰船检测方法
A Multi-domain Feature-guided Method for Unsupervised Ship Detection in SAR Images
摘要
Abstract
How to improve the ship detection performance with limited annotation samples in a synthetic aperture radar(SAR)image has always been a hot spot in SAR image processing.In this paper,a multi-domain feature-guided unsupervised domain adaptation method is proposed.The knowledge is transferred from the annotated source domain(optical images)to the unannotated target domain(SAR images),and thus the dependency on the labeled SAR images is reduced.At the same time,the frequency domain transfer module,attention area-enhanced(AAE)module,and adaptive weighted module are designed to narrow the domain gap between the optical and SAR image domains,improve the efficiency of feature alignment between the source and target domains,and enhance the capability of feature transfer under challenging samples.Extensive experiments are carried out on public published datasets.The results show that the proposed modules are 10%better than the baseline,and the overall network outperforms other state-of-the-art(SOTA)methods.关键词
域适应/合成孔径雷达(SAR)图像/光学图像/舰船检测/频域转换Key words
domain adaptation/synthetic aperture radar(SAR)image/optical image/ship detection/frequency domain conversion分类
信息技术与安全科学引用本文复制引用
陈亮,李健昊,何成,师皓..多域特征引导的无监督SAR图像舰船检测方法[J].上海航天（中英文）,2024,41(3):121-129,9.基金项目
国家自然科学基金(62101041) （62101041）
