After the revival of deep learning in computer vision in 2012, SAR ship detection comes into
the deep learning era too. The deep learning-based computer vision algorithms can work in …

This study adheres to a set of guidelines for performing an SLR. The mission of the SLR is to
find publications, publishers, deep learning types, improved and amended deep learning …

Ship detection from synthetic aperture radar (SAR) remote sensing images is essential for
monitoring water traffic and marine safety. Numerous methods for ship detection have been …

At present, deep learning has been widely used in SAR ship target detection, but the
accurate and real-time detection of multi-scale targets still faces tough challenges. CNN …

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 …

SAR ship detection and recognition are important components of the application of SAR
data interpretation, allowing for the continuous, reliable, and efficient monitoring of maritime …

Recently, deep learning has greatly promoted the development of synthetic aperture radar
(SAR) ship detection. But the detectors are usually heavy and computation intensive, which …

Recently, ship detection in synthetic aperture radar (SAR) images has received extensive
attention. Most of the current ship detectors preset dense anchor boxes to achieve spatial …

For the characteristics of synthetic aperture radar (SAR) images, such as the dense
arrangement of ship targets on shore, which are easily affected by land, the sparse …

The existing synthetic aperture radar (SAR) ship datasets have an imbalanced number of
inshore and offshore ship targets, and the number of small, medium and large ship targets …