The booming development of remote sensing images in many visual tasks has led to an
increasing demand for obtaining images with more precise details. However, it is impractical …

Deep Learning, and Deep Neural Networks in particular, have established themselves as
the new norm in signal and data processing, achieving state-of-the-art performance in …

Optical remote sensing imagery is at the core of many Earth observation activities. The
regular, consistent and global-scale nature of the satellite data is exploited in many …

Active fire detection in satellite imagery is of critical importance to the management of
environmental conservation policies, supporting decision-making and law enforcement. This …

Road extraction in remote sensing images is of great importance for a wide range of
applications. Because of the complex background, and high density, most of the existing …

About half of all optical observations collected via spaceborne satellites are affected by haze
or clouds. Consequently, cloud coverage affects the remote-sensing practitioner's …

The majority of optical observations acquired via spaceborne Earth imagery are affected by
clouds. While there is numerous prior work on reconstructing cloud-covered information …

The existence of clouds is one of the main factors that contributes to missing information in
optical remote sensing images, restricting their further applications for Earth observation, so …

In recent years, the rapid development of Earth observation technology has produced an
increasing growth in remote sensing big data, posing serious challenges for effective and …

Cloud detection is a crucial step in the optical satellite image processing pipeline for Earth
observation. Clouds in optical remote sensing images seriously affect the visibility of the …