Building detection from very high resolution (VHR) optical remote sensing images, which is
an essential but challenging task in remote sensing, has attracted increased attention in …

Recent advances in sensor technology are expected to lead to a greater use of wireless
sensor networks (WSNs) in industry, logistics, healthcare, etc. On the other hand, advances …

Detecting building rooftops with very high-resolution (VHR) images is an important issue in
many fields, including disaster management, urban planning, and climate change research …

Urban road extraction is important for the applications of urban planning and transportation.
High-resolution image (HRI) has been one of the most popular data sources for extracting …

Quickly and accurately extracting buildings from remote sensing images is essential for
urban planning, change detection, and disaster management applications. In particular …

Cloud coverage poses a significant challenge to optical image interpretation, degrading
ground information on Earth's surface. Synthetic aperture radar (SAR), with its ability to …

The current deep convolutional neural networks for very-high-resolution (VHR) remote-
sensing image land-cover classification often suffer from two challenges. First, the feature …

Building extraction from remote sensing images is extremely important for urban planning,
land-cover change analysis, disaster monitoring, and so on. With the growing diversity in …

Modern spacecraft are increasingly relying on machine learning (ML). However, physical
equipment in space is subject to various natural hazards, such as radiation, which may …

Accurate extraction of urban features such as buildings and roads lays the foundation for the
current trends of digital twins of urban systems to support planning, monitoring, navigation …