Convolutional neural networks (CNNs) have received widespread attention due to their
powerful modeling capabilities and have been successfully applied in natural language …

In deep learning research, self-supervised learning (SSL) has received great attention,
triggering interest within both the computer vision and remote sensing communities. While …

Images gathered from different satellites are vastly available these days due to the fast
development of remote sensing (RS) technology. These images significantly enhance the …

Change detection is a vibrant area of research in remote sensing. Thanks to increases in the
spatial resolution of remote sensing images, subtle changes at a finer geometrical scale can …

An attention mechanism assigns different weights to different features to help a model select
the features most valuable for accurate classification. However, the traditional attention …

Change detection (CD) of remote sensing (RS) images is one of the important problems in
earth observation, which has been extensively studied in recent years. However, with the …

Due to rich spectral and spatial information, the combination of hyperspectral and
multispectral images (MSIs) has been widely used for Earth observation, such as wetland …

As a fundamental application, change detection (CD) is widespread in the remote sensing
(RS) community. With the increase in the spatial resolution of RS images, high-resolution …

Remote sensing is a tool of interest for a large variety of applications. It is becoming
increasingly more useful with the growing amount of available remote sensing data …

Thanks to their capability of modeling global information, transformers have been recently
applied to change detection (CD) in remote sensing images. Generally, the changes in …