Record link: 
http://hdl.handle.net/20.500.12708/229589
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Title: 
Multi-branch Deep Learning Architecture for bathymetric LiDAR Point Cloud Classification
en
Citation: 
Asgharian Pournodrati, L., Mandlburger, G., & Soergel, U. (2026). Multi-branch Deep Learning Architecture for bathymetric LiDAR Point Cloud Classification. In ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (pp. 81–90). https://doi.org/10.5194/isprs-annals-XI-1-2026-81-2026
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Publisher DOI: 
10.5194/isprs-annals-XI-1-2026-81-2026
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Asgharian Pournodrati, Lida 
Mandlburger, Gottfried 
Soergel, Uwe 
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Organisational Unit: 
E120-07 - Forschungsbereich Photogrammetrie 
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Published in: 
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 
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Volume: 
XI-1-2026
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Date (published): 
3-Jul-2026
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Event name: 
IXXV ISPRS Congress 2026 “From Imagery to Understanding”, Commission I 
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Event date: 
4-Jul-2026 - 11-Jul-2026
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Event place: 
Toronto, Canada
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Number of Pages: 
10
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Peer reviewed: 
Yes
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Keywords: 
Feature Fusion; Laser Bathymetry; Semantic Labelling; Coastal Zone
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Research Areas: 
Environmental Monitoring and Climate Adaptation: 100%
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Science Branch: 
2074 - Geodäsie, Vermessungswesen: 70%
1020 - Informatik: 15%
1054 - Physische Geographie: 15%
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Appears in Collections:
Conference Paper

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