Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Lukas Lucks"'
Publikováno v:
ISPRS Open Journal of Photogrammetry and Remote Sensing, Vol 12, Iss , Pp 100058- (2024)
This paper introduces methods for monitoring rock slope movements in Alpine environments based on terrestrial images. The first method is a photogrammtric point cloud-based deformation analysis, relying on M3C2. Although effective in identifying larg
Externí odkaz:
https://doaj.org/article/8b7fd4ce039d4856b163d72c077940b5
Publikováno v:
Proceedings of the 19th International Conference on Signal Processing and Multimedia Applications.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4daabc4cc07d301a5a517719528762c2
https://doi.org/10.5220/0011335900003289
https://doi.org/10.5220/0011335900003289
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol IV-4-W9, Pp 35-42 (2019)
Accurate and robust positioning of vehicles in urban environments is of high importance for many applications (e.g. autonomous driving or mobile mapping). In the case of mobile mapping systems, a simultaneous mapping of the environment using laser sc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::909df26285419e0ad2f856c8c6a730f8
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-4-W9/35/2019/isprs-annals-IV-4-W9-35-2019.pdf
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-4-W9/35/2019/isprs-annals-IV-4-W9-35-2019.pdf
Accurate and robust positioning of vehicles in urban environments is of high importance for autonomous driving or mobile mapping. In mobile mapping systems, a simultaneous mapping of the environment using laser scanning and an accurate positioning us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d729ffef3bc296cc45db85e6224d012a
https://publica.fraunhofer.de/handle/publica/266217
https://publica.fraunhofer.de/handle/publica/266217
Zusammenfassung Diese Arbeit untersucht die Eignung und Übertragbarkeit von synthetisch erzeugten Trainingsdaten zur Detektion von Weizenähren mithilfe neuronaler Netze aus dem Bereich der semantischen Bildsegmentierung. Zur Erstellung dieser Daten
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9f9ff9296e48fba310753e871591537f
https://publica.fraunhofer.de/handle/publica/267880
https://publica.fraunhofer.de/handle/publica/267880
Publikováno v:
VISIGRAPP (1: GRAPP)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85a54ee57cade5b04918a61914326fe3
https://doi.org/10.5220/0008895600250037
https://doi.org/10.5220/0008895600250037
Publikováno v:
Communications in Computer and Information Science ISBN: 9783030415891
VISIGRAPP (Revised Selected Papers)
VISIGRAPP (Revised Selected Papers)
According to the United States National Centers for Environmental Information (NCEI), 2017 was one of the most expensive year of losses due to numerous weather and climate disaster events. To reduce the expenditures handling insurance claims and inte
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::faf9fd24a08fd6e2ad4d66ee4762f8cd
https://doi.org/10.1007/978-3-030-41590-7_21
https://doi.org/10.1007/978-3-030-41590-7_21
Land cover classification from airborne data is considered a challenging task in Remote Sensing. Even in the case of available elevation data, shadows and strong intra-class variations of appearances are abundant in urban terrain. In this paper, we p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32222d934bf8fdd1580c4573bb64ea99
https://publica.fraunhofer.de/handle/publica/258180
https://publica.fraunhofer.de/handle/publica/258180
Publikováno v:
Earth Resources and Environmental Remote Sensing/GIS Applications IX.
Semantic land cover classification of satellite images or airborne images is becoming increasingly important for applications like urban planning, road net analysis or environmental monitoring. Sensor orientations or varying illumination make classif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57449cf1766d0923ff141cb215a6c1d9
https://doi.org/10.1117/12.2325604
https://doi.org/10.1117/12.2325604
Publikováno v:
IGARSS
Derivation of training data for landcover classification is an important step in almost all supervised classification tasks. Manual annotation is very time-consuming, so it is useful to simplify and to support this process. We developed a semiautomat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ad6c3aa99f4e38c8043f9c082c651d6
https://doi.org/10.1109/igarss.2018.8518311
https://doi.org/10.1109/igarss.2018.8518311