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Smaller is better? Unduly nice accuracy assessments in roof detection using remote sensing data with machine learning and k-fold cross-validation.

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第一作者： Dávid,Abriha

第一单位： Department of Physical Geography and Geoinformatics, Faculty of Science and Technology, Institute of Geosciences, University of Debrecen, Egyetem tér 1, Debrecen, 4032, Hungary.

作者： Dávid,Abriha ^[1] ; Prashant K,Srivastava ^[2] ; Szilárd,Szabó ^[1]

作者单位： Department of Physical Geography and Geoinformatics, Faculty of Science and Technology, Institute of Geosciences, University of Debrecen, Egyetem tér 1, Debrecen, 4032, Hungary. ^[1] Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, 221005, India. ^[2]

关键词 Accuracy assessment Object-based pixel purity Post-classification Roof classification Salt-and-pepper effect Urban environment

DOI 10.1016/j.heliyon.2023.e14045

PMID 36915546

发布时间 2023-03-15

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Smaller is better? Unduly nice accuracy assessments in roof detection using remote sensing data with machine learning and k-fold cross-validation.

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Smaller is better? Unduly nice accuracy assessments in roof detection using remote sensing data with machine learning and k-fold cross-validation.

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