3D-ResNet-BiLSTM Model: A Deep Learning Model for County-Level Soybean Yield Prediction with Time-Series Sentinel-1, Sentinel-2 Imagery, and Daymet 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/Armin_Moghimi>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Mahdiyeh_Fathi>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Reza_Shah-Hosseini>
foaf:homepage	<http://dx.doi.org/doi.org%2F10.3390%2Frs15235551>
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dc:identifier	DBLP journals/remotesensing/FathiSM23 (xsd:string)
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dcterms:issued	2023 (xsd:gYear)
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foaf:maker	<https://dblp.l3s.de/d2r/resource/authors/Armin_Moghimi>
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swrc:month	December (xsd:string)
swrc:number	23 (xsd:string)
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rdfs:seeAlso	<https://doi.org/10.3390/rs15235551>
dc:title	3D-ResNet-BiLSTM Model: A Deep Learning Model for County-Level Soybean Yield Prediction with Time-Series Sentinel-1, Sentinel-2 Imagery, and Daymet Data. (xsd:string)
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