| 改进YOLOv5的SAR图像舰船目标检测 |
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| 引用本文： | 谭显东,彭辉. 改进YOLOv5的SAR图像舰船目标检测[J]. 计算机工程与应用, 2022, 58(4): 247-254. DOI: 10.3778/j.issn.1002-8331.2108-0308 |
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| 作者姓名： | 谭显东 彭辉 |
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| 作者单位： | 成都信息工程大学 软件工程学院，成都 610225 |
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| 基金项目： | 四川省科技计划资助项目(2019YJ0356)。 |
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| 摘 要： | 近年来针对合成孔径雷达(synthetic aperture radar,SAR)图像中缺乏颜色和纹理细节的舰船检测技术在深度学习领域中得到了广泛研究,利用深度学习技术可以有效避免传统的复杂特征设计,并且检测精度得到极大改善.针对舰船目标检测框具有高长宽比和密集排列问题,提出一种基于改进YOLOv5的目标检测方法.该方...
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| 关 键 词： | 合成孔径雷达(SAR) YOLOv5 舰船检测 坐标注意力机制 |
Improved YOLOv5 Ship Target Detection in SAR Image |
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| TAN Xiandong,PENG Hui. Improved YOLOv5 Ship Target Detection in SAR Image[J]. Computer Engineering and Applications, 2022, 58(4): 247-254. DOI: 10.3778/j.issn.1002-8331.2108-0308 |
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| Authors: | TAN Xiandong PENG Hui |
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| Affiliation: | School of Software Engineering, Chengdu University of Information Technology, Chengdu 610225, China |
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| Abstract: | In recent years, the ship detection technology for the lack of color and texture details in synthetic aperture radar（SAR） images has been extensively studied in the field of deep learning. The use of deep learning technology can effectively avoid traditional complex feature design, and the accuracy of detection is greatly improved. For the problems of high aspect ratio and dense arrangement of ship targets detection, a target detection method based on improved YOLOv5 is proposed. According to the characteristics of ship targets detection, the length and width of detection are taken into comprehensive consideration and the loss function curve is optimized, and the coordinate attention mechanism（CA） is combined to achieve high-speed and high-precision detection of ship targets while the model is lightweight. The experimental results show that：Compared with the original YOLOv5 method, the detection accuracy of this method is increased from 92.3% to 96.7%, the mAP index is increased from 92.5% to 97.2%, which is significantly better than the comparison method. By improving the detection frame loss function and feature extraction methods, the detection effect of ship targets in SAR images is improved. |
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| Keywords: | synthetic aperture radar(SAR) YOLOv5 ship detection coordinate attention mechanism |
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