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 …

Due to its great application value in the military and civilian fields, ship detection in synthetic
aperture radar (SAR) images has always attracted much attention. However, ship targets in …

Current synthetic aperture radar (SAR) ship classifiers using convolutional neural networks
(CNNs) offer state-of-the-art performance. Yet, they still have two defects potentially …

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 …

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 …

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 …

With the development of synthetic aperture radar (SAR) imaging and deep learning, SAR
ship detection based on convolutional neural networks (CNNs) has been extensively …

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 …