Interpretable deep learning for consistent large-scale urban population estimation using Earth observation data
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Published:2024-04
Issue:
Volume:128
Page:103731
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ISSN:1569-8432
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Container-title:International Journal of Applied Earth Observation and Geoinformation
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language:en
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Short-container-title:International Journal of Applied Earth Observation and Geoinformation
Author:
Doda SugandhaORCID,
Kahl Matthias,
Ouan Kim,
Obadic IvicaORCID,
Wang Yuanyuan,
Taubenböck HannesORCID,
Zhu Xiao XiangORCID
Reference60 articles.
1. Peeking inside the black-box: a survey on explainable artificial intelligence (XAI);Adadi;IEEE Access,2018
2. Arik, S.Ö., Pfister, T., 2021. Tabnet: Attentive interpretable tabular learning. In: Proceedings of the AAAI Conference on Artificial Intelligence. pp. 6679–6687.
3. LandScan;Bhaduri;Geoinformatics,2002
4. OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks;Boeing;Comput. Environ. Urban Syst.,2017
5. GHS-POP accuracy assessment: Poland and Portugal case study;Calka;Remote Sens.,2020