Building a Fully-Automatized Active Learning Framework for the Semantic Segmentation of Geospatial 3D Point Clouds
Crossref DOI link: https://doi.org/10.1007/s41064-024-00281-3
Published Online: 2024-04-03
Published Print: 2024-04
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Kölle, Michael https://orcid.org/0000-0002-5343-2021
Walter, Volker
Sörgel, Uwe
Funding for this research was provided by:
Universität Stuttgart
Text and Data Mining valid from 2024-04-01
Version of Record valid from 2024-04-03
Article History
Received: 25 September 2023
Accepted: 25 February 2024
First Online: 3 April 2024
Conflict of interest
: The authors declare that they have no conflict of interest.