Water body classification from high-resolution optical remote sensing (RS) images, aiming at
classifying whether each pixel of the image is water or not, has become a hot issue in the …

Water features (eg, water quantity and water quality) are one of the most important
environmental factors essential to improving climate-change resilience. Remote sensing …

Deep learning networks have recently demonstrated yielded impressive progress for multi-
exposure image fusion. However, how to restore realistic texture details while correcting …

Wildland fires are one of the most dangerous natural risks, causing significant economic
damage and loss of lives worldwide. Every year, millions of hectares are lost, and experts …

Weakly supervised semantic segmentation (WSSS) has gained significant popularity as it
relies only on weak labels such as image level annotations rather than the pixel level …

Water bodies extraction is important in water resource utilization and flood prevention and
mitigation. Remote sensing images contain rich information, but due to the complex spatial …

Water features are one of the most crucial environmental elements for strengthening climate-
change adaptation. Remote sensing (RS) technologies driven by artificial intelligence (AI) …

Water is a kind of vital natural resource, which acts as the lifeblood of the ecosystem and the
energy source for the living and production activities of humans. Regularly mapping the …

The unmanned aerial vehicle (UAV)-captured panoptic remote sensing images have great
potential to promote robotics-inspired intelligent solutions for land cover mapping, disaster …

Forests can be efficiently monitored by automatic semantic segmentation of trees using
satellite and/or aerial images. Still, several challenges can make the problem difficult …