<div class="csl-bib-body">
<div class="csl-entry">Gao, Y., & Zhao, H. (2023). Segment Anything Model for Refugee-Dwelling Extraction with Few Samples from High-Resolution Satellite Imagery. In <i>Proceedings of the 18th International Conference on Location Based Services</i> (pp. 87–92). https://doi.org/10.34726/5740</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/194765
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dc.identifier.uri
https://doi.org/10.34726/5740
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dc.description.abstract
Customizing Segment Anything Model (SAM) has recently attracted considerable attention in remote sensing domains. This study explores the performance of SAM-Adapter in refugee-dwelling extraction in three different refugee camps from high-resolution satellite images. The findings indicate that with scarce sample data, SAM-Adapter marginally outperforms other semantic segmentation models. This underscores SAM's promising potential for building extraction tasks when data is limited.
en
dc.language.iso
en
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
Segment Anything Model
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dc.subject
Dwelling Extraction
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dc.title
Segment Anything Model for Refugee-Dwelling Extraction with Few Samples from High-Resolution Satellite Imagery
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.rights.license
Creative Commons Attribution 4.0 International
en
dc.identifier.doi
10.34726/5740
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dc.contributor.affiliation
University of Salzburg, Austria
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dc.contributor.affiliation
University of Florida, United States of America (the)
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dc.relation.doi
10.34726/5400
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dc.description.startpage
87
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dc.description.endpage
92
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dc.rights.holder
Authors
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Proceedings of the 18th International Conference on Location Based Services
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tuw.relation.ispartof
10.34726/5400
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tuw.researchTopic.id
I5
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tuw.researchTopic.name
Visual Computing and Human-Centered Technology
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E000 - Technische Universität Wien
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dc.identifier.libraryid
AC17202176
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dc.description.numberOfPages
6
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dc.rights.identifier
CC BY 4.0
de
dc.rights.identifier
CC BY 4.0
en
tuw.event.name
18th International Conference on Location Based Services (LBS 2023)
