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

In recent years, object detection in Synthetic-Aperture Radar (SAR) images still faces many
challenges, especially for ship detection. Small or dense ships are vulnerable to the …

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

Deep learning methods have greatly promoted the ship detection performance in synthetic
aperture radar (SAR) images. However, due to the different imaging mechanisms and target …

Due to the capacity of full-time and full-weather working, synthetic aperture radar (SAR)
images have been frequently applied to ship detection. However, the interference of speckle …

Synthetic aperture radar (SAR) images of ships have complex background interference,
multi-scale targets, and irregular distribution characteristics. However, existing mainstream …

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 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 …

Ship detection in synthetic aperture radar (SAR) images is crucial for various applications in
both civilian and military domains. In recent years, there has been substantial progress in …

Recently, deep learning techniques have been successfully applied to SAR ship detection.
However, SAR ship detection is still a challenging task. First, ship targets in SAR images are …