High-Power Electromagnetic (HPEM) environments are capable of causing effects like malfunctions, performance degradation, interferences, and destructions in electronic and electrical systems. Due to the large plurality of ...

In this paper we investigate the potential of automatic supervised classification for urban hydrological applications. In particular, we contribute to runoff simulations using hydrodynamic urban drainage models. In order ...

Creating 3D models of the static environment is an important task for the advancement of driver assistance systems and autonomous driving. In this work, a static reference map is created from a Mobile Mapping “light detection ...

In this case study we compare cloud fractional cover measured by radiometers on polar satellites (AVHRR) and on one geostationary satellite (SEVIRI) to ground-based manual (SYNOP) and automated observations by a cloud ...

In this paper we propose a probabilistic supervised classification algorithm for LiDAR (Light Detection And Ranging) point clouds. Several object classes (i.e. ground, building and vegetation) can be separated reliably by ...

In this investigation, we address the task of airborne LiDAR point cloud labelling for urban areas by presenting a contextual classification methodology based on a Conditional Random Field (CRF). A two-stage CRF is set up: ...

Text classification is an essential task in natural language processing. While graph neural networks (GNNs) have successfully been applied to this problem both through graph classification and node classification approaches, ...

Rising consumption due to a growing world population and increasing prosperity, combined with a linear economic system have led to a sharp increase in garbage collection, general pollution of the environment and the threat ...

High resolution global irradiance time series are needed for accurate simulations of photovoltaic (PV) systems, since the typical volatile PV power output induced by fast irradiance changes cannot be simulated properly ...

Coastal areas are characterized by high spatial and temporal variability. In order to detect undesired changes at early stages, enabling rapid countermeasures to mitigate or minimize potential harm or hazard, a recurrent ...