哈尔滨工程大学学报2024，Vol.45Issue(3)：504-516,13.DOI:10.11990/jheu.202205018
基于改进CenterNet的轻量级无锚框SAR图像多尺度舰船检测算法
Lightweight and anchor-free frame method of multiscale ship detection based on improved CenterNet in SAR images
摘要
Abstract
A lightweight ship detection framework for SAR images without an anchor frame was constructed in this study,with the aim of addressing the problems of poor accuracy,low efficiency,and poor generalization of the mul-tiscale ship detection in a complex scene.In addition,a lightweight anchor-free frame method for ship detection in the SAR images based on the improved CenterNet was proposed to meet the real-time detection requirement of ships in the SAR images.The rapid and accurate positioning and detection of the ship in SAR images is achieved by pre-dicting the information of key points of the target and relevant attributes of the detection frame.A data augmentation method suitable for the SAR ship image was adopted to expand the training samples and solve the problem of scarci-ty of the SAR image samples,while multiscale training was introduced to enhance the model generalization perform-ance.The experimental results show that the proposed method has the advantages of high efficiency,high detection accuracy,and strong generalization performance,thereby realizing the real-time high-precision detection of the mul-tiscale ships in complicated scenes.关键词
合成孔径雷达图像/复杂场景/多尺度训练/舰船检测/改进CenterNet/轻量级/无锚框/数据增强Key words
SAR image/complicated scene/multiscale training/ship detection/improved CenterNet/lightweight/anchor-free frame/data augmentation分类
信息技术与安全科学引用本文复制引用
谢洪途,姜新桥,王国倩,谢恺..基于改进CenterNet的轻量级无锚框SAR图像多尺度舰船检测算法[J].哈尔滨工程大学学报,2024,45(3):504-516,13.基金项目
国家自然科学基金项目(62203465,62201614) （62203465,62201614）
广东省基础与应用基础研究基金项目(2023A1515011588,2021A1515010768) （2023A1515011588,2021A1515010768）
深圳市科技计划(202206193000001,20220815171723002). （202206193000001,20220815171723002）
