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Impollonia, Giorgio
17  Ergebnisse:
OpenAccess-Volltexte X
Personensuche X
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1

Field Plant Monitoring from Macro to Micro Scale: Feasibili..:

Vurro, Filippo ; Croci, Michele ; Impollonia, Giorgio...
Plants.  , 2023
Link: https://hdl.handle.net/2..
 
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2

UAV Remote Sensing for High-Throughput Phenotyping and for ..:

Impollonia, Giorgio ; Croci, Michele ; Ferrarini, Andrea...
https://edepot.wur.nl/574294.  , 2022
Link: https://research.wur.nl/..
 
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3

DB_miscanthus:

Impollonia, Giorgio
doi:10.5281/zenodo.6053787.  , 2022
Link: https://zenodo.org/recor..
 
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4

RTM Inversion through Predictive Equations for Multi-Crop L..:

Croci, Michele ; Impollonia, Giorgio ; Marcone, Andrea...
info:eu-repo/semantics/altIdentifier/wos/WOS:000894671100001.  , 2022
Link: https://hdl.handle.net/1..
 
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5

Moisture content estimation and senescence phenotyping of n..:

Impollonia, Giorgio ; Croci, Michele ; Martani, Enrico...
https://edepot.wur.nl/571209.  , 2022
Link: https://research.wur.nl/..
 
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6

RTM Inversion through Predictive Equations for Multi-Crop L..:

Michele Croci ; Giorgio Impollonia ; Andrea Marcone...
Farming Sustainability.  , 2022
Link: https://doi.org/10.3390/..
 
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7

Dynamic Maize Yield Predictions Using Machine Learning on M..:

Michele Croci ; Giorgio Impollonia ; Stefano Amaducci
info:eu-repo/semantics/altIdentifier/wos/WOS:000908639300001.  , 2022
Link: https://hdl.handle.net/1..
 
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8

Comparison of PROSAIL Model Inversion Methods for Estimatin..:

Giorgio Impollonia ; Michele Croci ; Henri Blandinières..
Remote Sensing in Agriculture and Vegetation.  , 2022
Link: https://doi.org/10.3390/..
 
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9

RTM Inversion through Predictive Equations for Multi-Crop L..:

Michele Croci ; Giorgio Impollonia ; Andrea Marcone...
https://www.mdpi.com/2073-4395/12/11/2835.  , 2022
Link: https://doi.org/10.3390/..
 
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10

agr-spectral-indices: v1.0.0:

Michele Croci ; Giorgio Impollonia ; Andrea Marcone.
https://github.com/MCroci/agr-spectral-indices/tree/agri-spectral-indices.  , 2022
Link: https://zenodo.org/recor..
 
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11

UAV Remote Sensing for High-Throughput Phenotyping and for ..:

Giorgio Impollonia ; Michele Croci ; Andrea Ferrarini...
https://www.mdpi.com/2072-4292/14/12/2927.  , 2022
Link: https://doi.org/10.3390/..
 
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12

Comparison of PROSAIL Model Inversion Methods for Estimatin..:

Giorgio Impollonia ; Michele Croci ; Henri Blandinières..
https://www.mdpi.com/2072-4292/14/22/5801.  , 2022
Link: https://doi.org/10.3390/..
 
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13

Impact of Training Set Size and Lead Time on Early Tomato C..:

Michele Croci ; Giorgio Impollonia ; Henri Blandinières..
https://dx.doi.org/10.3390/rs14184540.  , 2022
Link: https://doi.org/10.3390/..
 
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14

UAV Remote Sensing for High-Throughput Phenotyping and for ..:

Giorgio Impollonia ; Michele Croci ; Andrea Ferrarini...
Remote Sensing in Agriculture and Vegetation.  , 2022
Link: https://doi.org/10.3390/..
 
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15

Dynamic Maize Yield Predictions Using Machine Learning on M..:

Michele Croci ; Giorgio Impollonia ; Michele Meroni.
Remote Sensing Image Processing.  , 2022
Link: https://doi.org/10.3390/..
 
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