Interminable surveillance and reconnaissance through various sophisticated multispectral
detectors present threats to military equipment and manpower. However, a combination of …

Feature extraction is a crucial step for any automatic target recognition process, especially in
the interpretation of synthetic aperture radar (SAR) imagery. In order to obtain distinctive …

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 …

Optical confusion refers to a camouflage technique assimilated with the surroundings
through manipulating colors and patterns. With the advances in multispectral imagery …

Metamaterials have the powerful ability to freely control multiband electromagnetic (EM)
waves through elaborately designed “artificial atoms” and are hence in the limelight in …

Synthetic aperture radar (SAR) systems, which operate under a slant-viewing geometry,
inevitably entail shadow regions in the resulting radar image. Such shadow profiles contain …

Since Synthetic Aperture Radar (SAR) targets are full of coherent speckle noise, the
traditional deep learning models are difficult to effectively extract key features of the targets …

Dynamic thermal camouflage is an emerging technology that adjusts the thermal radiation
emitted by the surface of an object to match that emitted by the surroundings. Although …

This paper presents a novel double weight-based synthetic aperture radar (SAR) and
infrared (IR) sensor fusion method (DW-SIF) for automatic ground target recognition (ATR) …

Deep neural network (DNN)-based synthetic aperture radar automatic target recognition
(SAR ATR) methods have made great progress in recent years. However, the performance …