计算机技术与发展2026，Vol.36Issue(3)：59-67,9.DOI:10.20165/j.cnki.ISSN1673-629X.2025.0261
面向SAR图像船舶目标检测的多尺度聚合扩散网络
Multi-scale Aggregation Diffusion Network for SAR Ship Object Detection
摘要
Abstract
Although object detection has made significant progress,most methods designed for natural images degrade sharply when applied to SAR ship images due to complex background clutter and multi-scale object variations.To address these issues,we propose DMADNet,a diffusion-based multi-scale detection network tailored for SAR ship detection.To enhance the detection accuracy,a Multi-scale Aggregation Network(MANet)is designed.Its core design concept is the independent feature extraction and interactive fusion strategy,which builds a flexible and efficient information flow processing framework,highlights the target features,and significantly improves the detection performance in the reasoning stage.Meanwhile,the Context Aggregation Attention(CA-X)designed is integrated into the network in a parallel manner,which can effectively integrate long-distance context information.While ensuring the help of the global context for target discrimination,it avoids the interference of irrelevant backgrounds,thereby significantly improving the detection accuracy of ship targets in complex backgrounds.DMADNet achieved mean Average Precision(mAP)scores of 96.65％,93.03％,and 97.92％on the SAR Ship Detection Dataset(SSDD),the High-Resolution SAR Image Dataset(HRSID),and the SAR-Ship dataset,respectively,under an IoU threshold of 0.5.These results further demonstrate the model's robustness and excellent detection capability in complex environments.关键词
船舶目标检测/扩散模型/特征强化/合成孔径雷达图像/多尺度融合Key words
ship object detection/diffusion model/feature enhancement/synthetic aperture radar images/multi-scale fusion分类
信息技术与安全科学引用本文复制引用
郭耀武,王飞,陈云菲..面向SAR图像船舶目标检测的多尺度聚合扩散网络[J].计算机技术与发展,2026,36(3):59-67,9.基金项目
国家自然科学基金(62272426) （62272426）
山西省科技重大专项计划"揭榜挂帅"项目(202201150401021) （202201150401021）
山西省自然科学基金(202203021222027) （202203021222027）
