Deep learning-based detection methods have achieved great success in ship target
detection in synthetic aperture radar (SAR) images. However, due to the interference of …

Deep learning algorithms have been widely used in ship detection with synthetic aperture
radar (SAR). However, the complex background, clutter noise, and large span of ship sizes …

Ship detection is of great significance in the interpretation of synthetic aperture radar (SAR)
images. However, SAR generates inherent speckle noise when producing images, which …

Considering the difficulty of ship detection in Synthetic Aperture Radar (SAR) images lacking
color and texture details, we propose a method for SAR ship detection based on hierarchical …

Synthetic aperture radar (SAR) ship detection has been playing an increasingly essential
role in marine monitoring in recent years. The lack of detailed information about ships in …

The ship target detection technology in synthetic aperture radar (SAR) imaging plays an
important role in information warfare. However, due to the coherence of the system and the …

Recently, convolutional neural network based methods have been studied for ship detection
in optical remote sensing images. However, it is challenging to apply them to microwave …

Independent of daylight and weather conditions, synthetic aperture radar (SAR) images
have been widely used for ship monitoring. The traditional methods for SAR ship detection …

Ship detection is a challenging task for synthetic aperture radar (SAR) images. Ships have
arbitrary directionality and multiple scales in SAR images. Furthermore, there is a lot of …

A neural network-based object detection algorithm has the advantages of high accuracy and
end-to-end processing, and it has been widely used in synthetic aperture radar (SAR) ship …