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dc.contributor.authorHuang, Lanqing
dc.contributor.authorJohansson, Anna Malin Kristin
dc.contributor.authorHajnsek, Irena
dc.date.accessioned2024-10-17T13:24:41Z
dc.date.available2024-10-17T13:24:41Z
dc.date.issued2024-09-05
dc.description.abstractIn this study, we trained a supervised neural network for sea ice classification using X-band SAR images obtained during an Antarctic fieldwork campaign and applied it to Arctic X-band data acquired during sea ice fieldwork campaigns. The results revealed a pronounced correlation between the predicted sea ice class and measured snow depth in the Arctic. This correlation is likely attributed to the Arctic acquisitions taking place during the cold winter conditions characterized by thicker snow layers, which resemble conditions in Antarctica.en_US
dc.identifier.citationHuang, Johansson A M, Hajnsek I. Assessing the Transferability of Neural Network-Based Sea Ice Classification between the Arctic and Antarctic. IEEE International Geoscience and Remote Sensing Symposium proceedings. 2024en_US
dc.identifier.cristinIDFRIDAID 2277533
dc.identifier.doi10.1109/IGARSS53475.2024.10641661
dc.identifier.issn2153-6996
dc.identifier.issn2153-7003
dc.identifier.urihttps://hdl.handle.net/10037/35289
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.journalIEEE International Geoscience and Remote Sensing Symposium proceedings
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2024 The Author(s)en_US
dc.titleAssessing the Transferability of Neural Network-Based Sea Ice Classification between the Arctic and Antarcticen_US
dc.type.versionacceptedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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