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 …

Since only the spatial feature information of ship target is utilized, the current deep learning-
based synthetic aperture radar (SAR) ship detection approaches cannot achieve a …

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

With the booming of Convolutional Neural Networks (CNNs), CNNs such as VGG-16 and
ResNet-50 widely serve as backbone in SAR ship detection. However, CNN based …

With the development of synthetic aperture radar (SAR)-based imaging technology, SAR
ship detection has achieved notable breakthroughs. Due to the scale diversity and class …

Intelligent ship detection based on high-precision synthetic aperture radar (SAR) images
plays a vital role in ocean monitoring and maritime management. Denoising is an effective …

Synthetic aperture radar (SAR) is an active remote sensing system that possesses
characteristics such as all-weather capability and strong penetrability. In ship detection, SAR …

It is very difficult to detect multi-scale synthetic aperture radar (SAR) ships, especially under
complex backgrounds. Traditional constant false alarm rate methods are cumbersome in …

Synthetic aperture radar (SAR) ship detection is widely used in cutting-edge applications
such as environmental protection, traffic monitoring, search, and rescue. Lightweight …

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 …