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Titel:

SegmentationUQ

Dokumenttyp:
Forschungsdaten
Veröffentlichungsdatum:
17.05.2024
Verantwortlich:
Zhu, Xiaoxiang
Autorinnen / Autoren:
Wasif, Dawood (1; 2) ; Shahzad, Muhammad (1, 2) ; Wang, Yuanyuan (1) ; Zhu, Xiaoxiang (1)
Institutionszugehörigkeit:
1. Technical University of Munich
2. SEECS, National University of Sciences & Technology, Pakistan
Herausgeber:
TUM
Identifikator:
doi:10.14459/2024mp1741760.001
Konzept-DOI:
doi:10.14459/2024mp1741760
Enddatum der Datenerzeugung:
31.01.2024
Fachgebiet:
DAT Datenverarbeitung, Informatik; GEO Geowissenschaften
Quellen der Daten:
Simulationen / simulations; Abbildungen von Objekten / image of objects
Datentyp:
Bilder / images
Methode der Datenerhebung:
We render the data from 3D building models and very high resolution aerial images of Berlin, Germany in the software Blender with the Cycles engine with rendering settings emulating real-world environmental conditions closely. Images with different noise levels, noise distributions, and viewing angles of the sensors were rendered.
Beschreibung:
SegmentationUQ is a synthetic "error-free" benchmark dataset for semantic segmentation of building footprints and evaluation of uncertainty quantification methods. This proposed synthetic dataset not only contains labels of the building masks but also the reference aleatoric uncertainty given different noise level and noise type of the input images.
Links:

Additional contact if questions arise:  Wang, Yuanyuan y.wang@tum.de   

Schlagworte:
Semantic Segmentation; Uncertainty Quantification; Synthetic Data; Uncertainty Labels; Benchmark; Building Segmentation
Technische Hinweise:
Representative Dataset: View and download (39 GB total, 412 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1741760.rep):
rsync rsync://m1741760.rep@dataserv.ub.tum.de/m1741760.rep /

Entire Dataset: View and download (3,9 TB total, 40009 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1741760.001):
rsync rsync://m1741760.001@dataserv.ub.tum.de/m1741760.001/
Sprache:
en
Rechte:
by, http://creativecommons.org/licenses/by/4.0
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