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 …

Artificial ANNs (ANNs) are relatively new computational tools used in the development of
intelligent systems, some of which are inspired by biological ANNs, and have found …

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 …

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 …

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

This letter proposes a squeeze-and-excitation Laplacian pyramid network with dual-
polarization feature fusion (SE-LPN-DPFF) for ship classification in synthetic aperture radar …

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

Deep learning has offered new ideas in SAR ship target recognition. Although many
methods improve the recognition performance through the improvement of loss function and …

Machine learning methods for synthetic aperture radar (SAR) image automatic target
recognition (ATR) can be divided into two main types: traditional methods and deep learning …