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1 Ergebnisse
1
Einsatz von Deep Learning zur automatischen Detektion und K..:
Sesselmann, Maximilian
;
Stricker, Ronny
;
Eisenbach, Markus
AGIT -- AGIT Journal -- 2509-713X -- http://uri.gbv.de/document/gvk:ppn:865280894 -- 2864570-4 -- http://www.agit-journal.net/ -- http://www.bibliothek.uni-regensburg.de/ezeit/?2864570. , 2019
Link:
https://doi.org/10.14627/537669009
RT Journal T1 <Title>Einsatz von Deep Learning zur automatischen Detektion und Klassifikation von Fahrbahnschäden aus mobilen LiDAR-Daten ; Deep learning for automatic detection and classification of road damage from mobile LiDAR data</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftdbthueringen:oai:www.db-thueringen.de:dbt_mods_00044232&Exemplar=1&LAN=DE A1 Sesselmann, Maximilian A1 Stricker, Ronny A1 Eisenbach, Markus YR 2019 K1 article K1 ScholarlyArticle K1 ddc:004 K1 Mobile LiDAR -- Deep Learning -- Straßenzustandserfassung -- Road Condition Assessment JF AGIT -- AGIT Journal -- 2509-713X -- http://uri.gbv.de/document/gvk:ppn:865280894 -- 2864570-4 -- http://www.agit-journal.net/ -- http://www.bibliothek.uni-regensburg.de/ezeit/?2864570 LK http://dx.doi.org/https://doi.org/10.14627/537669009 DO https://doi.org/10.14627/537669009 SF ELIB - SuUB Bremen
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