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Turning Night into Day: The Creation and Validation of Synthetic Nighttime Visible Imagery Using the Visible Infrared Imaging Radiometer Suite (VIIRS) Day–Night Band (DNB) and Machine Learning

dc.contributor.authorPasillas, Chandra M.
dc.contributor.authorKummerow, Christian
dc.contributor.authorBell, Michael
dc.contributor.authorMiller, Steven D.
dc.date.accessioned2024-12-24T13:45:04Z
dc.date.available2024-12-24T13:45:04Z
dc.date.copyright01 Jul. 2024
dc.date.issued2024
dc.identifier.otheraies-AIES-D-23-0002.1.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4299545
dc.languageEnglish
dc.publisherAmerican Meteorological Society
dc.titleTurning Night into Day: The Creation and Validation of Synthetic Nighttime Visible Imagery Using the Visible Infrared Imaging Radiometer Suite (VIIRS) Day–Night Band (DNB) and Machine Learning
dc.typeJournal Paper
dc.journal.volume3
dc.journal.issue3
dc.journal.titleArtificial Intelligence for the Earth Systems
dc.identifier.doi10.1175/AIES-D-23-0002.1
dc.journal.lastpagee230002
dc.treeArtificial Intelligence for the Earth Systems:;2024:;volume( 003 ):;issue: 003
dc.contenttypeFulltext


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