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dc.contributor.authorSkjelvareid, Martin Hansen
dc.contributor.authorRinde, Eli
dc.contributor.authorHancke, Kasper
dc.contributor.authorBlix, Katalin
dc.contributor.authorHoarau, Galice Guillaume
dc.date.accessioned2023-11-06T12:17:35Z
dc.date.available2023-11-06T12:17:35Z
dc.date.issued2023-10-20
dc.description.abstractMarine macroalgae form underwater "blue forests" with several important functions. Hyperspectral imaging from unmanned aerial vehicles provides a rich set of spectral and spatial data that can be used to map the distribution of such macroalgae. Results from a study using 81 annotated hyper-spectral images from the Norwegian coast are presented. A U-net convolutional network was used for classification, and accuracies for all macroalgae classes were above 90%, indicating the potential of the method as an accurate tool for blue forest monitoring.en_US
dc.identifier.citationSkjelvareid, Rinde, Hancke, Blix, Hoarau. Mapping Marine Macroalgae along the Norwegian Coast Using Hyperspectral UAV Imaging and Convolutional Nets for Semantic Segmentation. IEEE International Geoscience and Remote Sensing Symposium proceedings. 2023en_US
dc.identifier.cristinIDFRIDAID 2191987
dc.identifier.doi10.1109/IGARSS52108.2023.10282809
dc.identifier.issn2153-6996
dc.identifier.issn2153-7003
dc.identifier.urihttps://hdl.handle.net/10037/31681
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.journalIEEE International Geoscience and Remote Sensing Symposium proceedings
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.titleMapping Marine Macroalgae along the Norwegian Coast Using Hyperspectral UAV Imaging and Convolutional Nets for Semantic Segmentationen_US
dc.type.versionacceptedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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