DENSE DOCKED SHIP DETECTION VIA SPATIAL GROUP-WISE ENHANCE ATTENTION IN SAR IMAGES

被引:17
作者
Wang, Xiaoya [1 ]
Cui, Zongyong [1 ]
Cao, Zongjie [1 ]
Dang, Sihang [1 ]
机构
[1] Univ Elect Sci & Technol China, Chengdu 611731, Sichuan, Peoples R China
来源
IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2020年
基金
中国国家自然科学基金;
关键词
Ship detection; SAR iamges; Anchor-free; Convolutional neural network; Dense docking;
D O I
10.1109/IGARSS39084.2020.9324162
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Target detection for dense docked SAR ships has always been a challenge. First of all, dense docked ships are generally in the port area, and the interference in the land area is large. Secondly, the adjacent ships are easily detected as a ship in the detection, or will be suppressed during the Non Maximal Suppression (NMS) process, causing the targets to be lost. This paper proposes a target detection method for dense docked ships based on CenterNet. At the same time, Spatial Group-wise Enhance (SGE) attention module is added to CenterNet in this paper. SGE reduces the amount of calculation by grouping channels, and at the same time strengthens the spatial features of each group to extract more semantic features. The enhanced feature map is sent to the detection network for dense docked SAR ship target detection. The proposed method is verified on the dataset SAR-ship-Dataset, and the experimental results show that the method in this paper has better detection performance for dense docked ships.
引用
收藏
页码:1244 / 1247
页数:4
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