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Coffee Global Quality Estimation Using Multilayer Perceptron

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Artificial Neural Networks

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Abstract

This application uses artificial neural networks for qualifying coffee batches or coffee brands from a set of sensors based on conductive polymers, which were developed by EMBRAPA (Brazilian Agricultural Research Corporation).

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, USP/EESC/SEL, University of São Paulo, São Carlos, São Paulo, Brazil

    Ivan Nunes da Silva, Danilo Hernane Spatti, Rogerio Andrade Flauzino, Luisa Helena Bartocci Liboni & Silas Franco dos Reis Alves

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  1. Ivan Nunes da Silva
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  2. Danilo Hernane Spatti
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  3. Rogerio Andrade Flauzino
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  4. Luisa Helena Bartocci Liboni
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  5. Silas Franco dos Reis Alves
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Correspondence to Ivan Nunes da Silva .

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da Silva, I.N., Hernane Spatti, D., Andrade Flauzino, R., Liboni, L.H.B., dos Reis Alves, S.F. (2017). Coffee Global Quality Estimation Using Multilayer Perceptron. In: Artificial Neural Networks . Springer, Cham. https://doi.org/10.1007/978-3-319-43162-8_11

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  • DOI: https://doi.org/10.1007/978-3-319-43162-8_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43161-1

  • Online ISBN: 978-3-319-43162-8

  • eBook Packages: EngineeringEngineering (R0)

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