Synthetic aperture radar (SAR) target detection plays a crucial role in both military and
civilian fields, attracting significant attention from researchers globally. CenterNet, a single …

It is very difficult to detect multi-scale synthetic aperture radar (SAR) ships, especially under
complex backgrounds. Traditional constant false alarm rate methods are cumbersome in …

Recently, in the field of synthetic aperture radar (SAR) ship detection, deep-learning-based
methods have made significant strides in terms of detection accuracy and speed. However …

Synthetic aperture radar (SAR) ship detection is widely used in cutting-edge applications
such as environmental protection, traffic monitoring, search, and rescue. Lightweight …

Thanks to the excellent feature representation capabilities of neural networks, target
detection methods based on deep learning are now widely applied in synthetic aperture …

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 …

Deep-learning technology has enabled remarkable results for ship detection in SAR images.
However, in view of the complex and changeable backgrounds of SAR ship images, how to …

Deep learning has proven to be highly effective in synthetic aperture radar (SAR) image
target detection. However, many latest deep learning models have predominantly focused …

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 …

Deep learning algorithms have been widely used in ship detection with synthetic aperture
radar (SAR). However, the complex background, clutter noise, and large span of ship sizes …