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 …

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 …

The use of deep learning-based techniques has improved the performance of synthetic
aperture radar (SAR) image-based applications, such as ship detection. However, all …

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 …

Object detection in synthetic aperture radar (SAR) images remains a challenging problem
due to the particular imaging mechanism of SAR systems. The sizes of targets are relatively …

Ship detection and classification in synthetic aperture radar (SAR) images play a vital role
for wide applications. Due to the unique SAR imaging mechanism, ship detection and …

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 …

Synthetic aperture radar (SAR) is an active microwave imaging sensor with the capability of
working in all-weather, all-day to provide high-resolution SAR images. Recently, SAR …

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 …

Deep learning has attracted increasing attention across a number of disciplines in recent
years. In the field of remote sensing, ship detection based on deep learning for synthetic …