DC Field
Value
Language
dc.contributor.author
Briechle, Sebastian
-
dc.contributor.author
Krzystek, Peter
-
dc.contributor.author
Vosselmann, George
-
dc.date.accessioned
2021-12-18T19:52:09Z
-
dc.date.available
2021-12-18T19:52:09Z
-
dc.date.issued
2021-12-01
-
dc.identifier.citation
<div class="csl-bib-body"> <div class="csl-entry">Briechle, S., Krzystek, P., &#38; Vosselmann, G. (2021). Deep Learning-based classification of tree species and standing dead trees using Silvi-Net. In <i>Proceedings of the SilviLaser Conference 2021</i> (pp. 160–162). https://doi.org/10.34726/wim.1966</div> </div>
-
dc.identifier.uri
http://hdl.handle.net/20.500.12708/19109
-
dc.identifier.uri
https://doi.org/10.34726/wim.1966
-
dc.language.iso
en
-
dc.relation.ispartofseries
Geowissenschaftliche Mitteilungen
-
dc.rights.uri
http://rightsstatements.org/vocab/InC/1.0/
-
dc.subject
CNN-based approach
en
dc.title
Deep Learning-based classification of tree species and standing dead trees using Silvi-Net
en
dc.type
Konferenzbeitrag
de
dc.type
Inproceedings
en
dc.rights.license
Urheberrechtsschutz
de
dc.rights.license
In Copyright
en
dc.identifier.doi
10.34726/wim.1966
-
dc.contributor.affiliation
Munich University of Applied Sciences, Germany
-
dc.contributor.affiliation
Munich University of Applied Sciences, Germany
-
dc.contributor.affiliation
University of Twente, Netherlands (the)
-
dc.relation.doi
10.34726/wim.1861
-
dc.relation.issn
1811-8380
-
dc.description.volume
104
-
dc.description.startpage
160
-
dc.description.endpage
162
-
dc.rights.holder
© Papers authors
-
dc.type.category
Full-Paper Contribution
-
tuw.booktitle
Proceedings of the SilviLaser Conference 2021
-
tuw.peerreviewed
true
-
tuw.relation.ispartof
10.34726/wim.1861
-
tuw.book.chapter
57
-
tuw.publication.orgunit
E120-07 - Forschungsbereich Photogrammetrie
-
dc.identifier.libraryid
AC17203335
-
dc.description.numberOfPages
3
-
tuw.relation.ispartoftuwseries
Geowissenschaftliche Mitteilungen
-
dc.rights.identifier
Urheberrechtsschutz
de
dc.rights.identifier
In Copyright
en
dc.description.sponsorshipexternal
German Federal Ministry of Education and Research (BMBF)
-
dc.relation.grantnoexternal
03FH004IX6
-
item.fulltext
with Fulltext
-
item.openairetype
conference paper
-
item.languageiso639-1
en
-
item.openaccessfulltext
Open Access
-
item.grantfulltext
open
-
item.mimetype
application/pdf
-
item.openairecristype
http://purl.org/coar/resource_type/c_5794
-
item.cerifentitytype
Publications
-
crisitem.author.dept
Munich University of Applied Sciences, Germany
-
crisitem.author.dept
Munich University of Applied Sciences, Germany
-
crisitem.author.dept
University of Twente
-
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