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 …

Deep learning-based ship-detection methods have recently achieved impressive results in
the synthetic aperture radar (SAR) community. However, numerous challenging issues …

In recent years, with the improvement of synthetic aperture radar (SAR) imaging resolution, it
is urgent to develop methods with higher accuracy and faster speed for ship detection in …

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 …

In light of recent advances in deep learning and Synthetic Aperture Radar (SAR) technology,
there has been a growing adoption of ship detection models that are based on deep …

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 …

Recently, deep-learning methods have been successfully applied to the ship detection in the
synthetic aperture radar (SAR) images. It is still a great challenge to detect multiscale SAR …

In recent years, target detection methods based on deep learning have achieved extensive
development in synthetic aperture radar (SAR) ship detection. However, training such …

Recently, in the field of synthetic aperture radar (SAR) ship detection, deep-learning-based
methods have made significant strides in terms of detection accuracy and speed. However …

Automatic ship target detection technique is a typical and meaningful application for
synthetic aperture radar (SAR) image interpretation. Nevertheless, the detection of ship …