Building footprint information is crucial for comprehending global urban development
processes. Deep learning algorithms have shown significant potential in building extraction …

This paper aims at achieving fine-grained building attribute segmentation in a cross-view
scenario ie using satellite and street-view image pairs. The main challenge lies in …

Deep neural networks have shown exemplary performance on semantic scene
understanding tasks on source domains but due to the absence of style diversity during …

Irrigation mapping plays a crucial role in effective water management essential for
preserving both water quality and quantity and is key to mitigating the global issue of water …

Enhancing the generalization capacity for semantic segmentation of aerial perception
systems for safety-critical applications is vital, especially for environments with low-light and …

Deep neural networks (DNNs) have shown exceptional performance when trained on well-
illuminated images captured by Electro-Optical (EO) cameras, which provide rich texture …

In recent years, segmentation algorithms utilizing deep learning have achieved outstanding
performance in medical image segmentation. However, accurately delineating small …

Segmentation of buildings in urban areas is crucial in many applications such as urban
planning, disaster response, and population mapping. The size and resolution of satellite …