<div class="csl-bib-body">
<div class="csl-entry">Asgharian Pournodrati, L., Mandlburger, G., & Soergel, U. (2026). Multi-branch Deep Learning Architecture for bathymetric LiDAR Point Cloud Classification. In <i>ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences</i> (pp. 81–90). https://doi.org/10.5194/isprs-annals-XI-1-2026-81-2026</div>
</div>
-
dc.identifier.uri
http://hdl.handle.net/20.500.12708/229589
-
dc.language.iso
en
-
dc.subject
Feature Fusion
en
dc.subject
Laser Bathymetry
en
dc.subject
Semantic Labelling
en
dc.subject
Coastal Zone
en
dc.title
Multi-branch Deep Learning Architecture for bathymetric LiDAR Point Cloud Classification
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
University of Stuttgart, Germany
-
dc.contributor.affiliation
University of Stuttgart, Germany
-
dc.description.startpage
81
-
dc.description.endpage
90
-
dc.type.category
Full-Paper Contribution
-
tuw.booktitle
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
-
tuw.container.volume
XI-1-2026
-
tuw.peerreviewed
true
-
tuw.researchTopic.id
E4
-
tuw.researchTopic.name
Environmental Monitoring and Climate Adaptation
-
tuw.researchTopic.value
100
-
tuw.publication.orgunit
E120-07 - Forschungsbereich Photogrammetrie
-
tuw.publisher.doi
10.5194/isprs-annals-XI-1-2026-81-2026
-
dc.description.numberOfPages
10
-
tuw.author.orcid
0009-0001-4986-2897
-
tuw.author.orcid
0000-0002-2332-293X
-
tuw.event.name
IXXV ISPRS Congress 2026 “From Imagery to Understanding”, Commission I
