With the soaring development of deep learning (DL) mechanisms in recent years,
convolution neural network (CNN)-based methods have been extensively investigated to …

The problem of multiscale ship detection in synthetic aperture radar (SAR) images has
received much attention with the development of deep convolutional neural networks …

This comprehensive review of concept-supported interpretation methods in Explainable
Artificial Intelligence (XAI) navigates the multifaceted landscape. As machine learning …

Most of the existing superpixel segmentation-based synthetic aperture radar (SAR) target
detection algorithms cannot keep the independence of small targets under complex …

The generation of superpixels is becoming a critical step in SAR image segmentation.
However, most studies on superpixels only focused on clustering methods without …

Synthetic aperture radar is widely applied to ship detection due to generating high-
resolution images under diverse weather conditions and its penetration capabilities, making …

To improve the salient region security and transmission efficiency of remote sensing images,
a multiple remote sensing image (MRSIs) encryption scheme based on saliency extraction …

Effective oil spill segmentation in synthetic aperture radar (SAR) images is critical for marine
oil pollution cleanup, and proper image representation contributes to effective learning for …

Nonlocal self-similarity is an important property of Synthetic Aperture Radar (SAR) images to
characterize the repetitiveness of features embodied by SAR images within nonlocal areas …

Because of high-resolution imaging in day and night and any weather condition, Synthetic
Aperture Radar (SAR) has various applications in remote sensing. Building detection is one …