Szczegóły

Tytuł artykułu

Improving sub-pixel imperviousness change prediction by ensembling heterogeneous non-linear regression models

Tytuł czasopisma

Geodesy and Cartography

Rocznik

2016

Wolumin

vol. 65

Numer

No 2

Autorzy

Słowa kluczowe

machine learning ; model ensembles ; sub-pixel classification ; impervious areas ; Landsat

Wydział PAN

Nauki Techniczne

Wydawca

Commitee on Geodesy PAS

Data

2016

Typ

Artykuły / Articles

Identyfikator

ISSN 2080-6736

Referencje

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DOI

10.1515/geocart-2016-0016

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