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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>High-resolution spatiotemporal assessment of solar potential from remote sensing data using deep learning</dc:title><dc:creator>Žalik,	Mitja	(Avtor)
	</dc:creator><dc:creator>Mongus,	Domen	(Avtor)
	</dc:creator><dc:creator>Lukač,	Niko	(Avtor)
	</dc:creator><dc:subject>deep learning</dc:subject><dc:subject>fully convolutional neural network</dc:subject><dc:subject>LiDAR data</dc:subject><dc:subject>digital elevation model</dc:subject><dc:subject>solar energy</dc:subject><dc:subject>solar potential</dc:subject><dc:publisher>Elsevier</dc:publisher><dc:date>2024</dc:date><dc:date>2024-01-26 07:31:58</dc:date><dc:type>Članek v reviji</dc:type><dc:identifier>86891</dc:identifier><dc:identifier>UDK: 004.8</dc:identifier><dc:identifier>COBISS_ID: 179585539</dc:identifier><dc:identifier>DOI: 10.1016/j.renene.2023.119868</dc:identifier><dc:identifier>ISSN pri članku: 1879-0682</dc:identifier><dc:language>sl</dc:language><dc:rights>© 2024 The Authors. Published by Elsevier Ltd.</dc:rights></metadata>
