Recently, convolutional neural networks (CNNs) have become popular for image
classification due to their effectiveness in computer vision tasks. Now, researchers are …

With the development of deep learning technology, the application of convolutional neural
network (CNN) and vision transformer (ViT) for polarimetric synthetic aperture radar …

Most existing polarimetric synthetic aperture radar (PolSAR) image classification methods
are only valid under the assumption of identical imaging platforms and terrain categories for …

Polarimetric synthetic aperture radar (PolSAR) images encompass valuable information that
can facilitate extensive land cover interpretation and generate diverse output products …

Deep learning models have been widely applied to Polarimetric Synthetic Aperture Radar
(PolSAR) image classification due to their excellent performance. However, unlike natural …

Following the remarkable success of deep convolutional neural networks (CNNs) in
computer vision, there has been an increasing focus on utilizing such networks for Synthetic …

Deep learning networks can automatically acquire high-level semantic features for
polarimetric SAR image classification, while it involves a blind learning procedure without …

Advantages of active imaging and providing more diverse features with multiple
polarizations have promoted the utilization of polarimetric synthetic aperture radar (PolSAR) …