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 …

Remote sensing change detection (RSCD), which aims to identify surface changes from
bitemporal images, is significant for many applications, such as environmental protection …

Detecting objects in remote sensing images (RSIs) using oriented bounding boxes (OBBs) is
flourishing but challenging, wherein the design of OBB representations is the key to …

Land cover change detection (LCCD) using remote sensing images (RSIs) plays an
important role in natural disaster evaluation, forest deformation monitoring, and wildfire …

Land cover change detection (LCCD) using bitemporal remote sensing images is a crucial
task for identifying the change areas on the Earth's surface. However, the utilization of …

Change detection (CD) is a hot research topic in the remote-sensing (RS) community. With
the increasing availability of high-resolution (HR) RS images, there is a growing demand for …

In recent years, few-shot segmentation (FSS) has received widespread attention from
scholars by virtue of its superiority in low-data regimes. Most existing research focuses on …

Fine-grained oriented object recognition (FGO) is a practical need for intellectually
interpreting remote sensing images. It aims at realizing fine-grained classification and …

Given two remote sensing images, the goal of visual change detection task is to detect
significantly changed areas between them. Existing visual change detectors usually adopt …

Practical applications ask for object detection models that achieve high performance at low
overhead. Knowledge distillation demonstrates favorable potential in this case by …