- 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
BibTeX