Zobrazeno 1 - 10 of 65 pro vyhledávání: '"Claus Brenner"'
1
Akademický článek
GPS-Aided Video Tracking
Autor: Udo Feuerhake, Claus Brenner, Monika Sester
Publikováno v: ISPRS International Journal of Geo-Information, Vol 4, Iss 3, Pp 1317-1335 (2015)
Tracking moving objects is both challenging and important for a large variety of applications. Different technologies based on the global positioning system (GPS) and video or radio data are used to obtain the trajectories of the observed objects. Ho
Externí odkaz: https://doaj.org/article/4613f589a3ee498281229cdeb135ce60
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2
Akademický článek
Integrity and Collaboration in Dynamic Sensor Networks
Autor: Steffen Schön, Claus Brenner, Hamza Alkhatib, Max Coenen, Hani Dbouk, Nicolas Garcia-Fernandez, Colin Fischer, Christian Heipke, Katja Lohmann, Ingo Neumann, Uyen Nguyen, Jens-André Paffenholz, Torben Peters, Franz Rottensteiner, Julia Schachtschneider, Monika Sester, Ligang Sun, Sören Vogel, Raphael Voges, Bernardo Wagner
Publikováno v: Sensors, Vol 18, Iss 7, p 2400 (2018)
Global Navigation Satellite Systems (GNSS) deliver absolute position and velocity, as well as time information (P, V, T). However, in urban areas, the GNSS navigation performance is restricted due to signal obstructions and multipath. This is especia
Externí odkaz: https://doaj.org/article/3310b784160c410eaa5f187dd3d00ccd
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3
MAXIMUM CONSENSUS LOCALIZATION USING LIDAR SENSORS
Autor: J. Axmann, Claus Brenner
Publikováno v: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-2-2021, Pp 9-16 (2021)
Real world localization tasks based on LiDAR usually face a high proportion of outliers arising from erroneous measurements and changing environments. However, applications such as autonomous driving require a high integrity in all of their component
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c17de74d260583ba77e4f41e8ee5a1e4
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-2-2021/9/2021/isprs-annals-V-2-2021-9-2021.pdf
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6
CREATING MULTI-TEMPORAL MAPS OF URBAN ENVIRONMENTS FOR IMPROVED LOCALIZATION OF AUTONOMOUS VEHICLES
Autor: Julia Schachtschneider, Claus Brenner
Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B2-2020, Pp 317-323 (2020)
The development of automated and autonomous vehicles requires highly accurate long-term maps of the environment. Urban areas contain a large number of dynamic objects which change over time. Since a permanent observation of the environment is impossi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02b93f14538ebe995cd7e14b79d9cdb8
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/317/2020/isprs-archives-XLIII-B2-2020-317-2020.pdf
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7
IMPROVING DEEP LEARNING BASED SEMANTIC SEGMENTATION WITH MULTI VIEW OUTLIER CORRECTION
Autor: M. Song, Claus Brenner, Torben Peters
Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B2-2020, Pp 711-716 (2020)
The goal of this paper is to use transfer learning for semi supervised semantic segmentation in 2D images: given a pretrained deep convolutional network (DCNN), our aim is to adapt it to a new camera-sensor system by enforcing predictions to be consi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5895bc0d2c7973b9895008d886492f48
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/711/2020/isprs-archives-XLIII-B2-2020-711-2020.pdf
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8
GEOMETRY-BASED POINT CLOUD CLASSIFICATION USING HEIGHT DISTRIBUTIONS
Autor: Claus Brenner, Monika Sester, F. Politz
Publikováno v: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-2-2020, Pp 259-266 (2020)
Semantic segmentation is one of the main steps in the processing chain for Airborne Laser Scanning (ALS) point clouds, but it is also one of the most labour intensive steps, as it requires many labelled examples to train a classifier. National mappin
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35586400cdd4395acb997f124de5c7d0
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-2-2020/259/2020/isprs-annals-V-2-2020-259-2020.pdf
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9
Conditional Adversarial Networks for Multimodal Photo-Realistic Point Cloud Rendering
Autor: Torben Peters, Claus Brenner
Publikováno v: Journal of photogrammetry, remote sensing and geoinformation science : PFG : Photogrammetrie, Fernerkundung, Geoinformation 88 (2020), Nr. 3-4
Journal of photogrammetry, remote sensing and geoinformation science : PFG : Photogrammetrie, Fernerkundung, Geoinformation
We investigate whether conditional generative adversarial networks (C-GANs) are suitable for point cloud rendering. For this purpose, we created a dataset containing approximately 150,000 renderings of point cloud–image pairs. The dataset was recor
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::08e3d344b7f4280196e5c2a12af7da54
https://doi.org/10.1007/s41064-020-00114-z
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10
Learning a Precipitation Indicator from Traffic Speed Variation Patterns
Autor: Claus Brenner, Monika Sester, Yu Feng
Publikováno v: Transportation Research Procedia 47 (2020)
It is common sense that traffic participants tend to drive slower under rain or snow conditions, which has been confirmed by many studies in the field of transportation research. When analyzing the relation between precipitation events and traffic sp
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::375359dbc0e770324507adec9b817e23
https://doi.org/10.1016/j.trpro.2020.03.090
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