2022 - Research.com Engineering and Technology in Austria Leader Award
His primary areas of study are Laser scanning, Remote sensing, Point cloud, Lidar and Terrain. His Laser scanning research includes themes of Segmentation, Computer vision, Artificial intelligence, Data mining and Raised-relief map. His research in Remote sensing intersects with topics in Radar, Computation and Laser, Optics.
Norbert Pfeifer has included themes like Benchmarking, Correctness, Statistics, Plot and Surface roughness in his Point cloud study. His study in Lidar is interdisciplinary in nature, drawing from both Plane, Forest inventory, Statistical parameter and k-nearest neighbors algorithm. His Terrain research is multidisciplinary, incorporating perspectives in Photogrammetry, Digital elevation model and Interpolation.
Norbert Pfeifer spends much of his time researching Remote sensing, Laser scanning, Point cloud, Lidar and Artificial intelligence. His studies deal with areas such as Terrestrial laser scanning, Terrain and Laser as well as Remote sensing. The Terrain study combines topics in areas such as Digital elevation model and Interpolation.
His Laser scanning study results in a more complete grasp of Optics. Norbert Pfeifer works mostly in the field of Point cloud, limiting it down to topics relating to Tree and, in certain cases, Forest inventory. His Artificial intelligence study incorporates themes from Computer vision and Pattern recognition.
Norbert Pfeifer mainly investigates Remote sensing, Point cloud, Lidar, Laser scanning and Artificial intelligence. His work on Digital elevation model and Photogrammetry as part of his general Remote sensing study is frequently connected to Data acquisition, thereby bridging the divide between different branches of science. His Point cloud research incorporates elements of Transformation, Algorithm, 3D reconstruction and Image segmentation.
His Lidar research incorporates themes from Ecology, Species richness, Habitat, Soil fertility and Diversity. Norbert Pfeifer incorporates Laser scanning and Complexity index in his research. His Artificial intelligence research includes themes of Machine learning and Pattern recognition.
Norbert Pfeifer mainly focuses on Remote sensing, Point cloud, Lidar, Laser scanning and Artificial intelligence. Norbert Pfeifer has researched Remote sensing in several fields, including 3D reconstruction and Radiometric calibration. His Point cloud research is multidisciplinary, incorporating perspectives in Subdivision, Acer platanoides, Evapotranspiration and Interception.
The study incorporates disciplines such as Image segmentation, Canopy, Cluster analysis, Photogrammetry and Ranging in addition to Lidar. The various areas that Norbert Pfeifer examines in his Laser scanning study include Image resolution, Maple, Noise, Sunrise and Sunset. His work in the fields of Artificial intelligence, such as Deep learning, Representation and Artificial neural network, intersects with other areas such as Set.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Determination of terrain models in wooded areas with airborne laser scanner data
K. Kraus;N. Pfeifer.
Isprs Journal of Photogrammetry and Remote Sensing (1998)
Correction of laser scanning intensity data: Data and model-driven approaches
Bernhard Höfle;Norbert Pfeifer.
Isprs Journal of Photogrammetry and Remote Sensing (2007)
A Comprehensive Automated 3D Approach for Building Extraction, Reconstruction, and Regularization from Airborne Laser Scanning Point Clouds
Peter Dorninger;Norbert Pfeifer.
ADVANCED DTM GENERATION FROM LIDAR DATA
K. Kraus;N. Pfeifer.
A Comparison of Evaluation Techniques for Building Extraction From Airborne Laser Scanning
M. Rutzinger;F. Rottensteiner;N. Pfeifer.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2009)
Segmentation of airborne laser scanning data using a slope adaptive neighborhood
Sagi Filin;Norbert Pfeifer.
Isprs Journal of Photogrammetry and Remote Sensing (2006)
Repetitive interpolation: A robust algorithm for DTM generation from Aerial Laser Scanner Data in forested terrain☆
Andrej Kobler;Norbert Pfeifer;Peter Ogrinc;Ljupčo Todorovski.
Remote Sensing of Environment (2007)
AUTOMATIC RECONSTRUCTION OF SINGLE TREES FROM TERRESTRIAL LASER SCANNER DATA
Norbert Pfeifer;Ben Gorte;Daniel Winterhalder.
Three-dimensional reconstruction of stems for assessment of taper, sweep and lean based on laser scanning of standing trees
Michael Thies;Norbert Pfeifer;Daniel Winterhalder;Ben G. H. Gorte.
Scandinavian Journal of Forest Research (2004)
DERIVATION OF DIGITAL TERRAIN MODELS IN THE SCOP++ ENVIRONMENT
Norbert Pfeifer;Philipp Stadler;Christian Briese.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: