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Poster (Scientific congresses and symposiums)
[Poster] Railway reconstruction from 3D point cloud using Deep Learning and Parametric Modeling
Yarroudh, Anass; Kharroubi, Abderrazzaq; Jeddoub, Imane et al.
2024 • Low-Cost 3D workshop
Peer reviewed
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https://hdl.handle.net/2268/325437
 

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Keywords :
Railway; CityJSON; Deep Learning; Point Cloud; LiDAR; 3D Reconstruction; 3D Modeling
Disciplines :
Computer science
Author, co-author :
Yarroudh, Anass  ;  Université de Liège - ULiège > Département de géographie > Geospatial Data Science and City Information Modelling (GeoScITY)
Kharroubi, Abderrazzaq  ;  Université de Liège - ULiège > Département de géographie > Geospatial Data Science and City Information Modelling (GeoScITY)
Jeddoub, Imane  ;  Université de Liège - ULiège > Département de géographie > Geospatial Data Science and City Information Modelling (GeoScITY)
Ballouch, Zouhair ;  Université de Liège - ULiège > Département de géographie > Geospatial Data Science and City Information Modelling (GeoScITY)
Billen, Roland  ;  Université de Liège - ULiège > Département de géographie > Geospatial Data Science and City Information Modelling (GeoScITY)
Language :
English
Title :
[Poster] Railway reconstruction from 3D point cloud using Deep Learning and Parametric Modeling
Publication date :
12 December 2024
Event name :
Low-Cost 3D workshop
Event organizer :
University of Brescia
Event place :
Brescia, Italy
Event date :
12-13 December 2024
Audience :
International
Peer reviewed :
Peer reviewed
Name of the research project :
TrackGen
Available on ORBi :
since 16 December 2024

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