Land-use and land-cover (LULC) classification using remote sensing imagery plays a vital
role in many environment modeling and land-use inventories. In this study, a hybrid feature …

The cropland field (CF) is the basic unit of agricultural production and a key element of
precision agriculture. High-precision delineations of CF boundaries provide a reliable data …

Feature representation has been widely used and developed recently. Multiscale features
have led to remarkable breakthroughs for representation learning process in many computer …

The Transition towards sustainable energy systems requires phasing out fossil fuels.
Hydropower is a key source of renewable energy and can contribute to reaching a 100 …

Deep learning algorithms have obtained great success in semantic segmentation of very
high-resolution (VHR) remote sensing images. Nevertheless, training these models …

Stroke is widely considered as the second most common cause of mortality. The adverse
consequences of stroke have led to global interest and work for improving the management …

Semantic segmentation is one of the significant tasks in understanding aerial images with
high spatial resolution. Recently, Graph Neural Network (GNN) and attention mechanism …

Historical aerial photographs provide salient information on the historical state of the
landscape. The exploitation of these archives is often limited by accessibility and the time …

Land cover is an important variable of the terrestrial ecosystem that provides information for
natural resources management, urban sprawl detection, and environment research. To …

Feature representation has received more and more attention in image classification.
Existing methods always directly extract features via convolutional neural networks (CNNs) …