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 …

Synthetic aperture radar (SAR) has all-day and all-weather characteristics and plays an
extremely important role in the military field. The breakthroughs in deep learning methods …

Since the number of superpixels is lower than that of pixels, superpixels can substantially
speed up subsequent processing steps and have been widely used in synthetic aperture …

Considering that synthetic aperture radar (SAR) images obtained directly after signal
processing are in the form of complex matrices, we propose a complex convolutional …

In this article, we propose an adaptive superpixel generation algorithm for synthetic aperture
radar (SAR) imagery, which is implemented based on fast density-based spatial clustering of …

Target recognition in synthetic aperture radar (SAR) imagery suffers from speckle noise and
geometric distortion brought by the range-based coherent imaging mechanism. A new SAR …

The Sentinel-1 mission provides a freely accessible opportunity for urban image
interpretation based on synthetic aperture radar (SAR) data with a specific resolution, which …

The ghost phenomenon in synthetic aperture radar (SAR) imaging is primarily caused by
azimuth or range ambiguities, which cause difficulties in SAR target detection application. To …

In this paper, a new Region-based Convolutional Neural Networks (RCNN) method is
proposed for target recognition in large scene synthetic aperture radar (SAR) images. To …

In order to realise the fast detection of ships in synthetic aperture radar (SAR) images, a
detection method combining visual saliency and a cascade convolutional neural network …