Uwe Stilla spends much of his time researching Artificial intelligence, Computer vision, Remote sensing, Synthetic aperture radar and Feature extraction. His study ties his expertise on Pattern recognition together with the subject of Artificial intelligence. Uwe Stilla interconnects Orientation and Level of detail in the investigation of issues within Remote sensing.
His research integrates issues of Image sensor, Radar imaging, Computational science and Signal processing in his study of Synthetic aperture radar. He has researched Feature extraction in several fields, including Rural area, Light scattering and Filter. His study on Image segmentation is often connected to Traffic analysis as part of broader study in Segmentation.
Uwe Stilla mainly investigates Artificial intelligence, Computer vision, Remote sensing, Point cloud and Pattern recognition. His work investigates the relationship between Artificial intelligence and topics such as Lidar that intersect with problems in Ranging. His Computer vision study frequently draws connections between adjacent fields such as Focus.
His work on Synthetic aperture radar, Remote sensing, Interferometric synthetic aperture radar and Layover as part of general Remote sensing study is frequently linked to High resolution, bridging the gap between disciplines. His work deals with themes such as Inverse synthetic aperture radar and Radar imaging, which intersect with Synthetic aperture radar. The Point cloud study combines topics in areas such as Data mining, Photogrammetry, Point, Voxel and Laser scanning.
His main research concerns Artificial intelligence, Point cloud, Computer vision, Pattern recognition and Segmentation. His research investigates the link between Artificial intelligence and topics such as Graph that cross with problems in Smoothing. His Point cloud research incorporates elements of Data mining, Artificial neural network, Photogrammetry, Lidar and Point.
His Lidar research is multidisciplinary, relying on both Focus, Ranging, Histogram and Laser scanning. His study in Pattern recognition is interdisciplinary in nature, drawing from both Graphical model, Random forest and Probabilistic logic. His biological study spans a wide range of topics, including Convolutional neural network and Cluster analysis.
His primary areas of investigation include Artificial intelligence, Point cloud, Computer vision, Pattern recognition and Voxel. His study explores the link between Artificial intelligence and topics such as Laser scanning that cross with problems in Lidar. His Point cloud study integrates concerns from other disciplines, such as Graph, Data mining, Photogrammetry, Transformation and Algorithm.
His research in the fields of Matching, Orientation and Change detection overlaps with other disciplines such as Building information modeling. His Pattern recognition study combines topics from a wide range of disciplines, such as Graphical model and Collinearity. His Voxel research incorporates themes from RANSAC and Graph based.
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.
3D segmentation of single trees exploiting full waveform LIDAR data
J. Reitberger;Cl. Schnörr;P. Krzystek;U. Stilla.
Isprs Journal of Photogrammetry and Remote Sensing (2009)
Deep Learning Earth Observation Classification Using ImageNet Pretrained Networks
Dimitrios Marmanis;Mihai Datcu;Thomas Esch;Uwe Stilla.
IEEE Geoscience and Remote Sensing Letters (2016)
Analysis of full waveform LIDAR data for the classification of deciduous and coniferous trees
J. Reitberger;P. Krzystek;U. Stilla.
International Journal of Remote Sensing (2008)
Classification With an Edge: Improving Semantic Image Segmentation with Boundary Detection
Dimitrios Marmanis;Dimitrios Marmanis;Konrad Schindler;Jan Dirk Wegner;Silvano Galliani.
Isprs Journal of Photogrammetry and Remote Sensing (2018)
SEMANTIC SEGMENTATION OF AERIAL IMAGES WITH AN ENSEMBLE OF CNNS
Dimitrios Marmanis;Dimitrios Marmanis;Jan D. Wegner;Silvano Galliani;Konrad Schindler.
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2016)
Range determination with waveform recording laser systems using a Wiener Filter
Boris Jutzi;Uwe Stilla.
Isprs Journal of Photogrammetry and Remote Sensing (2006)
Vehicle Detection in Very High Resolution Satellite Images of City Areas
Jens Leitloff;Stefan Hinz;Uwe Stilla.
IEEE Transactions on Geoscience and Remote Sensing (2010)
Airborne Vehicle Detection in Dense Urban Areas Using HoG Features and Disparity Maps
Sebastian Tuermer;Franz Kurz;Peter Reinartz;Uwe Stilla.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2013)
Potential and limits of InSAR data for building reconstruction in built-up areas
U. Stilla;U. Soergel;U. Thoennessen.
Isprs Journal of Photogrammetry and Remote Sensing (2003)
Machine Learning Comparison between WorldView-2 and QuickBird-2-Simulated Imagery Regarding Object-Based Urban Land Cover Classification
Tessio Novack;Thomas Esch;Hermann Kux;Uwe Stilla.
Remote Sensing (2011)
Profile was last updated on December 6th, 2021.
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