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SpectraNet–53: A deep residual learning architecture for predicting soluble solids content with VIS–NIR spectroscopy |
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Titel: |
SpectraNet–53: A deep residual learning architecture for predicting soluble solids content with VIS–NIR spectroscopy |
Auteur: |
Martins, J.A. Guerra, R. Pires, R. Antunes, M.D. Panagopoulos, T. Brázio, A. Afonso, A.M. Silva, L. Lucas, M.R. Cavaco, A.M. |
Verschenen in: |
Computers and electronics in agriculture |
Paginering: |
Jaargang 197 () nr. C pagina's p. |
Jaar: |
2022 |
Inhoud: |
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Uitgever: |
The Authors |
Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
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