In recent years, with the improvement of synthetic aperture radar (SAR) imaging resolution, it
is urgent to develop methods with higher accuracy and faster speed for ship detection in …

Recently, methods based on deep learning have been successfully applied to ship detection
for synthetic aperture radar (SAR) images. However, most current ship detection networks …

In recent years, the rapid development of Deep Learning (DL) has provided a new method
for ship detection in Synthetic Aperture Radar (SAR) images. However, there are still four …

Recently, deep learning-based methods have brought new ideas for ship detection in
synthetic aperture radar (SAR) images. However, several challenges still exist: 1) deep …

Due to the rapid development of chip technology and deep learning revolution, many ship
detection frameworks for synthetic aperture radar (SAR) imagery based on convolutional …

More convolutional neural network (CNN) methods are widely utilized for ship detection in
synthetic aperture radar (SAR) images. Nevertheless, there are still some problems that …

With the booming of Convolutional Neural Networks (CNNs), CNNs such as VGG-16 and
ResNet-50 widely serve as backbone in SAR ship detection. However, CNN based …

Deep learning-based detection methods have achieved great success in ship target
detection in synthetic aperture radar (SAR) images. However, due to the interference of …

Recently, deep-learning methods have been successfully applied to the ship detection in the
synthetic aperture radar (SAR) images. It is still a great challenge to detect multiscale SAR …

Convolutional neural networks (CNNs) have achieved milestones in object detection of
synthetic aperture radar (SAR) images. Recently, vision transformers and their variants have …