Accuracy evaluation of convolutional neural network classification algorithms for building identification in rural and urban areas from very-high-resolution satellite imagery in Jambi, Indonesia

Accurate land cover data are essential to a reliable decision-making process; therefore, researchers have turned to novel land cover classification algorithms employing machine learning on high-resolution satellite imagery to improve classification accuracy. The experiment presented in this paper a...

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Detaylı Bibliyografya

Asıl Yazarlar:	Daniel Nugroho, Muhammad Dimyati, Laswanto
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	Nicolaus Copernicus University in Toruń 2022-12-01
Seri Bilgileri:	Bulletin of Geography. Socio-Economic Series
Konular:	convolutional neural network land cover building classification satellite imagery
Online Erişim:	https://apcz.umk.pl/BGSS/article/view/35666
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