Change detection (CD) in remote sensing (RS) imagery is a pivotal method for detecting
changes in the Earth's surface, finding wide applications in urban planning, disaster …

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 …

The integration of Artificial Intelligence (AI) and Satellite Remote Sensing in Land Cover
Change Detection (LCCD) has gained increasing significance in scientific discovery and …

The Segment Anything Model (SAM) has shown impressive performance when applied to
natural image segmentation. However, it struggles with geographical images like aerial and …

Segment Anything Model (SAM) is drastically accelerating the speed and accuracy of
automatically segmenting and labeling large Red-Green-Blue (RGB) imagery datasets …

The interactive segmentation task consists in the creation of object segmentation masks
based on user interactions. The most common way to guide a model towards producing a …

Semantic segmentation of remote sensing imagery plays a pivotal role in extracting precise
information for diverse down-stream applications. Recent development of the Segment …

Change detection in remote sensing imagery is vital for Earth monitoring but faces
challenges such as background complexity and pseudo-changes. Effective interaction …

When a strong earthquake occurs, roads are the lifelines of rescue. The rapid development
of high-resolution satellite imaging platforms has made the application of remote sensing …

Water, indispensable for life and central to ecosystems, human activities, and climate
dynamics, requires rapid and accurate monitoring. This is vital for sustaining ecosystems …