Ship detection in synthetic aperture radar (SAR) images is becoming a research hotspot. In
recent years, as the rise of artificial intelligence, deep learning has almost dominated SAR …

Military, agricultural, and urban planning have all made extensive use of SAR/ISAR in the
realm of remote sensing. SAR/ISAR images are more capable of identifying the details of the …

Thanks to the excellent feature representation capabilities of neural networks, deep learning-
based methods perform far better than traditional methods on target detection tasks such as …

This paper introduces a novel Synthetic Aperture Radar (SAR) specific deep learning
framework for complex-valued SAR images. The conventional deep convolutional neural …

Ship target detection in synthetic aperture radar (SAR) images is essential for many
applications in marine monitoring and port security. Though considerable developments …

When an early warning radar installed in a spaceborne platform works in a down-looking
mode to detect a low-altitude flying target, the severely broadened main-lobe clutter cannot …

Synthetic aperture radar (SAR) ship detection is sensitive to the interference of inshore
background, disturbance of strong wind and waves. The similar textures of the neighbor …

SAR images play a crucial role in ship detection across diverse scenarios due to their all-
day, all-weather characteristics. However, detecting SAR ship targets poses inherent …

The ELVD (Ensemble-based Lenet VGGNet and DropoutNet) model is used in this paper to
examine hypothetical principles and theoretical identification of a real-time image …

In the framework of maritime surveillance, vessel detection techniques based on
spaceborne synthetic aperture radar (SAR) images have promoted extensive applications …