SAR Ship Detection Dataset (SSDD) is the first open dataset that is widely used to research
state-of-the-art technology of ship detection from Synthetic Aperture Radar (SAR) imagery …

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 …

Ship classification in synthetic aperture radar (SAR) images is a fundamental and significant
step in ocean surveillance. Recently, with the rise of deep learning (DL), modern abstract …

Synthetic aperture radar (SAR) is playing an important role in maritime domain awareness.
As a fundamental ocean mission, SAR ship detection can offer high-quality services for …

Synthetic-aperture radar (SAR) image target detection is widely used in military, civilian and
other fields. However, existing detection methods have low accuracy due to the limitations …

The ability to deal with intra and inter-modality features has been critical to the development
of RGB-D salient object detection. While many works have advanced in leaps and bounds in …

Most of the existing synthetic aperture radar (SAR) ship instance segmentation models do
not achieve mask interaction or offer limited interaction performance. Besides, their …

Existing instance segmentation models mostly pay less attention to the targeted
characteristics of ships in synthetic aperture radar (SAR) images, which hinders further …

Ship detection plays a crucial role in marine security in remote sensing imagery. This paper
discusses about a deep learning approach to detect the ships from satellite imagery. The …

Fast and high-accuracy detection of underwater targets based on side scan sonar images
has great potential for marine fisheries, underwater security, marine mapping, underwater …