Automatic target recognition (ATR) for military applications is one of the core processes
toward enhancing intelligence and autonomously operating military platforms. Spurred by …

This article proposes a multiscale convolutional neural network (CNN) based on component
analysis (CA-MCNN) for synthetic aperture radar (SAR) automatic target recognition (ATR) …

Tremendous progress has been made in object recognition with deep convolutional neural
networks (CNNs), thanks to the availability of large-scale annotated dataset. With the ability …

Abstract SAR Automatic Target Recognition (ATR) is a key task in microwave remote
sensing. Recently, Deep Neural Networks (DNNs) have shown promising results in SAR …

In the remote sensing image processing field, the synthetic aperture radar (SAR) target-
detection methods based on convolutional neural networks (CNNs) have gained remarkable …

Synthetic aperture radar automatic target recognition (SAR-ATR) has made great progress
in recent years. Most of the established recognition methods are supervised, which have …

The scattering signatures of a synthetic aperture radar (SAR) target image will be highly
sensitive to different azimuth angles/poses, which aggravates the demand for training …

The single shot multibox detector (SSD), a proposal-free method based on convolutional
neural network (CNN), has recently been proposed for target detection and has found …

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 …

Synthetic aperture radar (SAR) automatic target recognition (ATR) is an essential field in
SAR application. However, a sufficient number of labeled training SAR images for each …