Evaluating the Performance of PRISMA Shortwave Infrared Imaging Sensor for Mapping Hydrothermally Altered and Weathered Minerals Using the Machine Learning Paradigm. | 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/Himanshu_Govil>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Manika_Gupta>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Neelam_Agrawal>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Prashant_K._Srivastava>
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foaf:homepage	<https://doi.org/10.3390/rs15123133>
dc:identifier	DBLP journals/remotesensing/AgrawalGMGS23 (xsd:string)
dc:identifier	DOI doi.org%2F10.3390%2Frs15123133 (xsd:string)
dcterms:issued	2023 (xsd:gYear)
swrc:journal	<https://dblp.l3s.de/d2r/resource/journals/remotesensing>
rdfs:label	Evaluating the Performance of PRISMA Shortwave Infrared Imaging Sensor for Mapping Hydrothermally Altered and Weathered Minerals Using the Machine Learning Paradigm. (xsd:string)
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foaf:maker	<https://dblp.l3s.de/d2r/resource/authors/Prashant_K._Srivastava>
swrc:month	June (xsd:string)
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dc:title	Evaluating the Performance of PRISMA Shortwave Infrared Imaging Sensor for Mapping Hydrothermally Altered and Weathered Minerals Using the Machine Learning Paradigm. (xsd:string)
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