Cover Image

From Historical OpenStreetMap data to customized training samples for geospatial machine learning

Wu, Z, Li, H., Zipf, A. (2020). From Historical OpenStreetMap data to customized training samples for geospatial machine learning - - - In: Minghini, M., Coetzee, S., Juhász, L., Yeboah, G., Mooney, P., Grinberger, A.Y. (Eds.). Proceedings of the Academic Track at the State of the Map 2020 Online...

Full description

Saved in:
Bibliographic Details
Main Authors: Wu, Zhaoyan (Author) , Li, Hao (Author) , Zipf, Alexander (Author)
Format: Chapter/Article Conference Paper
Language:English
Published: July 4, 2020
Edition:Version v1
In: Zenodo
Year: 2020, Pages: 9-10
DOI:10.5281/zenodo.3923040
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.5281/zenodo.3923040
Verlag, lizenzpflichtig, Volltext: https://zenodo.org/records/3923040
Get full text
Author Notes:Zhaoyan Wu, Hao Li1, and Alexander Zipf
Description
Summary:Wu, Z, Li, H., Zipf, A. (2020). From Historical OpenStreetMap data to customized training samples for geospatial machine learning - - - In: Minghini, M., Coetzee, S., Juhász, L., Yeboah, G., Mooney, P., Grinberger, A.Y. (Eds.). Proceedings of the Academic Track at the State of the Map 2020 Online Conference, July 4-5 2020. Available at https://zenodo.org/communities/sotm-2020
Item Description:Gesehen am 19.02.2026
Aus: Minghini, M., Coetzee, S., Juhász, L., Yeboah, G., Mooney, P., Grinberger, A.Y. (Eds.). Proceedings of the Academic Track at the State of the Map 2020 Online Conference, July 4-5 2020. Available at https://zenodo.org/communities/sotm-2020
Physical Description:Online Resource
DOI:10.5281/zenodo.3923040

Similar Items