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Browsing by Subject "Random processes"

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Automatic classification of aerial imagery for urban hydrological applications

Paul, A.; Yang, C.; Breitkopf, U.; Liu, Y.; Wang, Z.; Rottensteiner, F.; Wallner, M.; Verworn, A.; Heipke, C. (Göttingen : Copernicus GmbH, 2018)

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 ...
Contextual classification of point clouds using a two-stage CRF

Niemeyer, Joachim; Rottensteiner, Franz; Sörgel, Uwe; Heipke, Christian (Göttingen : Copernicus GmbH, 2015)

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: ...
Cycle counting of roller bearing oscillations – case study of wind turbine individual pitching system

Stammler, Matthias; Reuter, Andreas; Poll, Gerhard (Amsterdam [u.a.] : Elsevier Science, 2018)

The amplitude, frequency and number of oscillating movements have a significant impact on the possible damage modes of rolling bearings. Changes in amplitude change both the fatigue and wear risk of the raceways. In order ...
Hierarchical higher order crf for the classification of airborne lidar point clouds in urban areas

Niemeyer, Joachim; Rottensteiner, Franz; Sörgel, Uwe; Heipke, Christian (Göttingen : Copernicus GmbH, 2016)

We propose a novel hierarchical approach for the classification of airborne 3D lidar points. Spatial and semantic context is incorporated via a two-layer Conditional Random Field (CRF). The first layer operates on a point ...
Monitoring concepts for coastal areas using lidar data

Schmidt, Alena; Rottensteiner, Franz; Sörgel, Uwe (Göttingen : Copernicus GmbH, 2013)

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 ...
Multi-source hierarchical conditional random field model for feature fusion of remote sensing images and LiDAR data

Zhang, Z.; Yang, M.Y.; Zhoua, M. (Katlenburg-Lindau : Copernicus Publications, 2013)

Feature fusion of remote sensing images and LiDAR points cloud data, which have strong complementarity, can effectively play the advantages of multi-class features to provide more reliable information support for the remote ...
On the number of iterations required by von Neumann addition

Grübel, Rudolf; Reimers, Anke (Cambridge : Cambridge University Press, 2001)

We investigate the number of iterations needed by an addition algorithm due to Burks et al. if the input is random. Several authors have obtained results on the average case behaviour, mainly using analytic techniques based ...
A two-layer Conditional Random Field model for simultaneous classification of land cover and land use

Albert, Lena; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2014)

This paper proposes a two-layer Conditional Random Field model for simultaneous classification of land cover and land use. Both classification tasks are integrated into a unified graphical model, which is reasonable due ...

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