Polarization can provide information largely uncorrelated with the spectrum and intensity.
Therefore, polarimetric imaging (PI) techniques have significant advantages in many fields …

Advancement in remote sensing technology and microwave sensors explores the
applications of remote sensing in different fields. Microwave remote sensing encompasses …

With the significant development of practicability in deep learning and the ultra-high-speed
information transmission rate of 5G communication technology will overcome the barrier of …

Deep learning in remote sensing has received considerable international hype, but it is
mostly limited to the evaluation of optical data. Although deep learning has been introduced …

Traditionally, nonlinear data processing has been approached via the use of polynomial
filters, which are straightforward expansions of many linear methods, or through the use of …

This authoritative resource presents a comprehensive illustration of modern Artificial
Intelligence/Machine Learning (AI/ML) technology for radio frequency (RF) data exploitation …

Restricted by the observation condition, synthetic aperture radar (SAR) automatic target
classification based on deep learning usually suffers from insufficient training samples. To …

Due to the advantages of Synthetic Aperture Radar (SAR), the study of Automatic Target
Recognition (ATR) has become a hot topic. Deep learning, especially in the case of a …

In recent years, convolutional neural networks (CNNs) have drawn considerable attention
for the analysis of synthetic aperture radar (SAR) data. In this study, major subareas of SAR …

Synthetic aperture radar (SAR) image classification using deep neural network has drawn
great attention, which generally requires various layers of deep model for feature learning …