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 …

Synthetic Aperture Radar (SAR), as a microwave sensor that can sense a target all day or
night under all-weather conditions, is of great significance for detecting water resources …

Automated water body detection from satellite imagery is a fundamental stage for urban
hydrological studies. In recent years, various deep convolutional neural network (DCNN) …

Deep learning has been widely used in automatic target recognition (ATR) for synthetic
aperture radar (SAR) recently. However, most of the studies are based on the network …

Water detection from SAR imagery has significant values, such as the flood monitoring and
environmental protection. Nowadays, significant progress has been achieved in water …

The use of deep learning for water extraction requires precise pixel-level labels. However, it
is very difficult to label high-resolution remote-sensing images at the pixel level. Therefore …

Driven by the urgent demand for flood monitoring, water resource management and
environmental protection, water-body detection in remote sensing imagery has attracted …

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 proliferation of massive polarimetric Synthetic Aperture Radar (SAR) data helps
promote the development of SAR image interpretation. Due to the advantages of powerful …

As an important remote sensing means, synthetic aperture radar (SAR) has many
superiorities to other sensors. How to effectively detect and locate ships in SAR images is …