Simultaneous Ship Detection and Orientation Estimation in SAR Images Based on Attention Module and Angle Regression

Sensors
Jizhou WangWeiwei Jiang

Abstract

Ship detection and angle estimation in SAR images play an important role in marine surveillance. Previous works have detected ships first and estimated their orientations second. This is time-consuming and tedious. In order to solve the problems above, we attempt to combine these two tasks using a convolutional neural network so that ships may be detected and their orientations estimated simultaneously. The proposed method is based on the original SSD (Single Shot Detector), but using a rotatable bounding box. This method can learn and predict the class, location, and angle information of ships using only one forward computation. The generated oriented bounding box is much tighter than the traditional bounding box and is robust to background disturbances. We develop a semantic aggregation method which fuses features in a top-down way. This method can provide abundant location and semantic information, which is helpful for classification and location. We adopt the attention module for the six prediction layers. It can adaptively select meaningful features and neglect weak ones. This is helpful for detecting small ships. Multi-orientation anchors are designed with different sizes, aspect ratios, and orientations. These can consid...Continue Reading

References

Feb 13, 2008·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·A BanerjeeR Chellappa
Jun 14, 2016·IEEE Transactions on Pattern Analysis and Machine Intelligence·Shaoqing RenJian Sun
Aug 27, 2016·Sensors·Xiangguang LengHuanxin Zou

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