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 …

Deep learning-based methods have achieved great success in target detection tasks of
computer vision, but when it comes to Synthetic Aperture Radar (SAR) image ship detection …

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 …

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 ship-detection methods have recently achieved impressive results in
the synthetic aperture radar (SAR) community. However, numerous challenging issues …

The ship target detection technology in synthetic aperture radar (SAR) imaging plays an
important role in information warfare. However, due to the coherence of the system and the …

In light of recent advances in deep learning and Synthetic Aperture Radar (SAR) technology,
there has been a growing adoption of ship detection models that are based on deep …

Most synthetic aperture radar (SAR) ship detectors based on convolutional neural networks
(CNNs) needed preset anchor boxes to object classification and bounding box coordinate …

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 …

Nowadays, the intricate nature of synthetic aperture radar (SAR) ship scenes, coupled with
the presence of multiscale targets, poses a significant challenge in detection accuracy …