福建电脑2024，Vol.40Issue(7)：53-57,5.DOI:10.16707/j.cnki.fjpc.2024.07.010
复杂场景SAR图像的船舰目标快速检测研究
Research on Fast Detection of Complex SAR Ship Targets Based on Improved YOLOv3 and Attention Mechanism
摘要
Abstract
SAR images in complex scenes are easily affected by terrain and strong scattering interference.To improve the efficiency and accuracy of ship target detection algorithms,this paper proposes a detection network scheme based on improved YOLOv3 and attention mechanism.The detection network mainly consists of the target screening network P-FCN and the target precise detection network S-SSD.P-FCN is a lightweight fully convolutional network used for rapid screening of ship targets.S-SSD is an improved YOLOv3 network that achieves precise detection of ship targets through a multi-level feature fusion system combined with dual channel attention mechanism CBAM and P-FCN for ship target localization.The experimental results show that the algorithm proposed in this paper has good detection performance for ship targets in complex SAR images.关键词
合成孔径雷达图像/船舰目标/快速检测算法Key words
Synthetic Aperture Radar Images/Ship Targets/Fast Detection Algorithm分类
信息技术与安全科学引用本文复制引用
曹红..复杂场景SAR图像的船舰目标快速检测研究[J].福建电脑,2024,40(7):53-57,5.基金项目
本文得到浙江省教育厅科研项目"基于改进YOLOv3与注意力机制的复杂SAR图像船舰快速检测研究"(No.Y202249939)资助. （No.Y202249939）
