Abstract
With the development of depth learning and synthetic aperture radar (Synthetic Aperture Radar, SAR) technology, SAR image target detection based on convolution neural network (convolutional neural network, CNN) has achieved certain results. However, there are still problems in SAR detection of near-shore ship targets in complex environments. For improving the detection performance of the algorithm, the detection rate of SAR image near shore ship targets in complex environment is improved. This paper proposes an algorithm for SAR image ship target detection in complex environment. The algorithm first uses convolution neural network for coastal segmentation, and SAR image ship target detection through the results of coastal segmentation. The experimental results show that the algorithm has efficient detection ability for SAR image near-shore ship target detection in complex environment.
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