Change detection is an essential and widely utilized task in remote sensing that aims to
detect and analyze changes occurring in the same geographical area over time, which has …

Brain-inspired algorithms have become a new trend in next-generation artificial intelligence.
Through research on brain science, the intelligence of remote sensing algorithms can be …

Satellite video is an emerging type of earth observation tool, which has attracted increasing
attention because of its application in dynamic analysis. However, most studies only focus …

Vision foundation models (VFMs), such as the segment anything model (SAM), allow zero-
shot or interactive segmentation of visual contents; thus, they are quickly applied in a variety …

Recent change detection (CD) methods focus on the extraction of deep change semantic
features. However, existing methods overlook the fine-grained features and have the poor …

Flood events are often accompanied by rainy weather, which limits the applicability of optical
satellite images, whereas synthetic aperture radar (SAR) is less sensitive to weather and …

Change detection (CD) is a hot topic and has been applied in many fields. Very high
resolution (VHR) images contain the rich spatial information, and are widely used in CD …

Deep learning has achieved great success in remote sensing image change detection (CD).
However, most methods focus only on the changed regions of images and cannot accurately …

Change detection (CD) is a critical task to observe and analyze dynamic processes of land
cover. Although numerous deep-learning (DL)-based CD models have performed …

Convolutional neural networks (CNN) and Transformers have made impressive progress in
the field of remote sensing change detection (CD). However, both architectures have their …