Waterloo Urban Scene Dataset: an annotation-efficient dataset for urban scene classification with minimal supervision

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published

Published in:: Abstracts of the ICA
Vol. 10.2025 (12.12.2025), art. no. 104, p. 1-2
Volume:: 10.2025
Publication date:: 12.12.2025
URN:: urn:nbn:de:0307-20260130-000-4
DOI:: 10.5194/ica-abs-10-104-2025
Language:: English
Type of Resource:: Text
Extent:: 1 Online-Ressource (Seite 1-2, 865,77 kB) : 1 Illustration, 1 Textdatei (PDF)
Keywords:: waterloo urban scene dataset; weakly supervised learning; semi-supervised learning; annotation-efficient; Datensatz zur städtischen Szenerie von Waterloo; Überwachtes Lernen^GND; Teilüberwachtes Lernen^GND; schwach überwachtes Lernen; annotierungseffizient
DDC subject of DNB:: 520 Astronomy & allied sciences
URL:: https://doi.org/10.5194/ica-abs-10-104-2025
URL:: https://ica-abs.copernicus.org/articles/10/104/2025/
Link to Raw Object:: https://ica-abs.copernicus.org/articles/10/104/2025/ica-abs-10-104-2025.pdf
Hosting institution:: University of Waterloo (UW) [CA]
Hosting institution:: Internationale Forschungseinrichtungen
Statement of responsibility:: Hongjie He, Yiqing Wu, Xuanchen Liu, Wenyi Shen, Shene Abdalla, Jianing Xu, Mingming Guo, Jonathan Li
Bibliographic notes:: Published in: Abstracts of the ICA, Volume 10, 2025 - 32nd International Cartographic Conference (ICC 2025); 17–22 August 2025, Vancouver, Canada; Editors: Mir Abolfazl Mostafavi, Jonathan Li, and Emmanuel Stefanakis | https://ica-abs.copernicus.org/articles/10/index.html