Towards crop traits estimation from hyperspectral data: evaluation of neural network models trained with real multi-site data or synthetic RTM simulations

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Bibliographic Details
Main Authors: Lorenzo Parigi, Gabriele Candiani, Ignazio Gallo, Piero Toscano, Mirco Boschetti
Format: Article
Language:English
Published: Polish Information Processing Society 2024-10-01
Series:Annals of computer science and information systems
Online Access:https://annals-csis.org/Volume_39/drp/pdf/4108.pdf
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author Lorenzo Parigi
Gabriele Candiani
Ignazio Gallo
Piero Toscano
Mirco Boschetti
author_facet Lorenzo Parigi
Gabriele Candiani
Ignazio Gallo
Piero Toscano
Mirco Boschetti
author_sort Lorenzo Parigi
collection DOAJ
format Article
id doaj-art-3c9a15ea619f43e19dcf1bda3cd477fd
institution Kabale University
issn 2300-5963
language English
publishDate 2024-10-01
publisher Polish Information Processing Society
record_format Article
series Annals of computer science and information systems
spelling doaj-art-3c9a15ea619f43e19dcf1bda3cd477fd2025-08-20T03:24:56ZengPolish Information Processing SocietyAnnals of computer science and information systems2300-59632024-10-013947548410.15439/2024F4108Towards crop traits estimation from hyperspectral data: evaluation of neural network models trained with real multi-site data or synthetic RTM simulationsLorenzo ParigiGabriele CandianiIgnazio GalloPiero ToscanoMirco Boschettihttps://annals-csis.org/Volume_39/drp/pdf/4108.pdf
spellingShingle Lorenzo Parigi
Gabriele Candiani
Ignazio Gallo
Piero Toscano
Mirco Boschetti
Towards crop traits estimation from hyperspectral data: evaluation of neural network models trained with real multi-site data or synthetic RTM simulations
Annals of computer science and information systems
title Towards crop traits estimation from hyperspectral data: evaluation of neural network models trained with real multi-site data or synthetic RTM simulations
title_full Towards crop traits estimation from hyperspectral data: evaluation of neural network models trained with real multi-site data or synthetic RTM simulations
title_fullStr Towards crop traits estimation from hyperspectral data: evaluation of neural network models trained with real multi-site data or synthetic RTM simulations
title_full_unstemmed Towards crop traits estimation from hyperspectral data: evaluation of neural network models trained with real multi-site data or synthetic RTM simulations
title_short Towards crop traits estimation from hyperspectral data: evaluation of neural network models trained with real multi-site data or synthetic RTM simulations
title_sort towards crop traits estimation from hyperspectral data evaluation of neural network models trained with real multi site data or synthetic rtm simulations
url https://annals-csis.org/Volume_39/drp/pdf/4108.pdf
work_keys_str_mv AT lorenzoparigi towardscroptraitsestimationfromhyperspectraldataevaluationofneuralnetworkmodelstrainedwithrealmultisitedataorsyntheticrtmsimulations
AT gabrielecandiani towardscroptraitsestimationfromhyperspectraldataevaluationofneuralnetworkmodelstrainedwithrealmultisitedataorsyntheticrtmsimulations
AT ignaziogallo towardscroptraitsestimationfromhyperspectraldataevaluationofneuralnetworkmodelstrainedwithrealmultisitedataorsyntheticrtmsimulations
AT pierotoscano towardscroptraitsestimationfromhyperspectraldataevaluationofneuralnetworkmodelstrainedwithrealmultisitedataorsyntheticrtmsimulations
AT mircoboschetti towardscroptraitsestimationfromhyperspectraldataevaluationofneuralnetworkmodelstrainedwithrealmultisitedataorsyntheticrtmsimulations