Evaluating capabilities of machine learning algorithms for aquatic vegetation classification in temperate wetlands using multi-temporal Sentinel-2 data. | D2R Server publishing the DBLP Bibliography Database, hosted at L3S Research Center

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dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Erika_Piaser>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Paolo_Villa>
foaf:homepage	<http://dx.doi.org/doi.org%2F10.1016%2Fj.jag.2023.103202>
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dc:identifier	DBLP journals/aeog/PiaserV23 (xsd:string)
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dcterms:issued	2023 (xsd:gYear)
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rdfs:label	Evaluating capabilities of machine learning algorithms for aquatic vegetation classification in temperate wetlands using multi-temporal Sentinel-2 data. (xsd:string)
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swrc:pages	103202 (xsd:string)
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dc:title	Evaluating capabilities of machine learning algorithms for aquatic vegetation classification in temperate wetlands using multi-temporal Sentinel-2 data. (xsd:string)
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