Bayesian Unsupervised Machine Learning Approach to Segment Arctic Sea Ice Using SMOS Data

Geophysical research letters : GRL 48(6), e2020GL091285 (2021). doi:10.1029/2020GL091285 : Published by Wiley, Hoboken, NJ

Bibliographic Details
Main Authors: Herbert, Christoph, Camps, Adriano, Wellmann, Jan Florian, Vall-llossera, Mercedes
Format: Text
Language:English
Published: RWTH Aachen University 2021
Subjects:
550
Arctic
Sea ice
Online Access:https://dx.doi.org/10.18154/rwth-2021-03755
https://publications.rwth-aachen.de/record/817192
id ftdatacite:10.18154/rwth-2021-03755
record_format openpolar
spelling ftdatacite:10.18154/rwth-2021-03755 2023-05-15T14:47:56+02:00 Bayesian Unsupervised Machine Learning Approach to Segment Arctic Sea Ice Using SMOS Data Herbert, Christoph Camps, Adriano Wellmann, Jan Florian Vall-llossera, Mercedes 2021 https://dx.doi.org/10.18154/rwth-2021-03755 https://publications.rwth-aachen.de/record/817192 en eng RWTH Aachen University https://dx.doi.org/10.1029/2020gl091285 550 Text Journal article article-journal ScholarlyArticle 2021 ftdatacite https://doi.org/10.18154/rwth-2021-03755 https://doi.org/10.1029/2020gl091285 2021-11-05T12:55:41Z Geophysical research letters : GRL 48(6), e2020GL091285 (2021). doi:10.1029/2020GL091285 : Published by Wiley, Hoboken, NJ Text Arctic Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic 550
spellingShingle 550
Herbert, Christoph
Camps, Adriano
Wellmann, Jan Florian
Vall-llossera, Mercedes
Bayesian Unsupervised Machine Learning Approach to Segment Arctic Sea Ice Using SMOS Data
topic_facet 550
description Geophysical research letters : GRL 48(6), e2020GL091285 (2021). doi:10.1029/2020GL091285 : Published by Wiley, Hoboken, NJ
format Text
author Herbert, Christoph
Camps, Adriano
Wellmann, Jan Florian
Vall-llossera, Mercedes
author_facet Herbert, Christoph
Camps, Adriano
Wellmann, Jan Florian
Vall-llossera, Mercedes
author_sort Herbert, Christoph
title Bayesian Unsupervised Machine Learning Approach to Segment Arctic Sea Ice Using SMOS Data
title_short Bayesian Unsupervised Machine Learning Approach to Segment Arctic Sea Ice Using SMOS Data
title_full Bayesian Unsupervised Machine Learning Approach to Segment Arctic Sea Ice Using SMOS Data
title_fullStr Bayesian Unsupervised Machine Learning Approach to Segment Arctic Sea Ice Using SMOS Data
title_full_unstemmed Bayesian Unsupervised Machine Learning Approach to Segment Arctic Sea Ice Using SMOS Data
title_sort bayesian unsupervised machine learning approach to segment arctic sea ice using smos data
publisher RWTH Aachen University
publishDate 2021
url https://dx.doi.org/10.18154/rwth-2021-03755
https://publications.rwth-aachen.de/record/817192
geographic Arctic
geographic_facet Arctic
genre Arctic
Sea ice
genre_facet Arctic
Sea ice
op_relation https://dx.doi.org/10.1029/2020gl091285
op_doi https://doi.org/10.18154/rwth-2021-03755
https://doi.org/10.1029/2020gl091285
_version_ 1766319043756687360

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