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 …

Convolutional neural network (CNN)-based deep learning (DL) is a powerful, recently
developed image classification approach. With origins in the computer vision and image …

Synthetic aperture radar (SAR) satellites can provide microwave remote sensing images
without weather and light constraints, so they are widely applied in the maritime monitoring …

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 …

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 …

Ship detection from synthetic aperture radar (SAR) imagery is a fundamental and significant
marine mission. It plays an important role in marine traffic control, marine fishery …

Recently, deep learning techniques have been extensively used to detect ships in synthetic
aperture radar (SAR) images. The majority of modern algorithms can achieve successful …

Influenced by the imaging mechanism, the occurrence of interference clutter in synthetic
aperture radar (SAR) renders the identification of false alarms using detectors challenging …

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 …