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Advances in Machine Learning Techniques Can Assist Across a Variety of Stages in Sea Ice Applications

dc.contributor.authorEayrs, Clare
dc.contributor.authorLee, Won Sang
dc.contributor.authorJin, Emilia
dc.contributor.authorLemieux, Jean-François
dc.contributor.authorMassonnet, François
dc.contributor.authorVancoppenolle, Martin
dc.contributor.authorZampieri, Lorenzo
dc.contributor.authorBennetts, Luke G.
dc.contributor.authorBlockley, Ed
dc.contributor.authorChung, Eui-Seok
dc.contributor.authorFraser, Alexander D.
dc.contributor.authorHam, Yoo-geun
dc.contributor.authorIm, Jungho
dc.contributor.authorKim, Baek-min
dc.contributor.authorKim, Beong-H
dc.date.accessioned2024-12-24T14:42:17Z
dc.date.available2024-12-24T14:42:17Z
dc.date.copyright01 Mar. 2024
dc.date.issued2024
dc.identifier.otherbams-BAMS-D-23-0332.1.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4301195
dc.languageEnglish
dc.publisherAmerican Meteorological Society
dc.titleAdvances in Machine Learning Techniques Can Assist Across a Variety of Stages in Sea Ice Applications
dc.typeJournal Paper
dc.journal.volume105
dc.journal.issue3
dc.journal.titleBulletin of the American Meteorological Society
dc.identifier.doi10.1175/BAMS-D-23-0332.1
dc.journal.fristpageE527
dc.journal.lastpageE531
dc.treeBulletin of the American Meteorological Society:;2024:;volume( 105 ):;issue: 003
dc.contenttypeFulltext


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