Integrating VGI contributions for gully mapping using Kalman filter and machine learning
The codes and datsets included are related to experiments and results conducted to integrate different lines digitized by volunteers using Kalman filter with changing amount of input lines. Three approaches are included: i) Kalman filtering integration to investigate the role of basemaps and a numbe...
Gespeichert in:
| Hauptverfasser: | , , , , |
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| Dokumenttyp: | Datenbank Forschungsdaten |
| Sprache: | Englisch |
| Veröffentlicht: |
Heidelberg
Universität
2024-02-19
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| DOI: | 10.11588/data/UHSQG0 |
| Schlagworte: | |
| Online-Zugang: | Resolving-System, kostenfrei, Volltext: https://doi.org/10.11588/data/UHSQG0 Verlag, kostenfrei, Volltext: https://heidata.uni-heidelberg.de/dataset.xhtml?persistentId=doi:10.11588/data/UHSQG0 
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| Verfasserangaben: | Miguel Vallejo Orti, Katharina Anders, Oliubikum Ajali, Olaf Bubenzer, Bernhard Höfle |
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| 245 | 1 | 0 | |a Integrating VGI contributions for gully mapping using Kalman filter and machine learning |c Miguel Vallejo Orti, Katharina Anders, Oliubikum Ajali, Olaf Bubenzer, Bernhard Höfle |
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| 500 | |a Gesehen am 13.05.2024 | ||
| 520 | |a The codes and datsets included are related to experiments and results conducted to integrate different lines digitized by volunteers using Kalman filter with changing amount of input lines. Three approaches are included: i) Kalman filtering integration to investigate the role of basemaps and a number of contributions, ii) Kalman filtering coupled with a self-learning stratergy and, iii) a cross-training strategy. (2024-01-03) | ||
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| 787 | 0 | 8 | |i Forschungsdaten zu |a Vallejo Orti, Miguel, 1983 - |t Integrating multi-user digitising actions for mapping gully outlines using a combined approach of Kalman filtering and machine learning |d 2024 |w (DE-627)1880834146 |
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