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Comparison of latent variable-based and artificial intelligence methods for impurity detection in PET recycling from NIR hyperspectral images

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Comparison of latent variable-based and artificial intelligence methods for impurity detection in PET recycling from NIR hyperspectral images

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Galdón-Navarro, B.; Prats-Montalbán, JM.; Cubero-García, S.; Blasco Ivars, J.; Ferrer, A. (2018). Comparison of latent variable-based and artificial intelligence methods for impurity detection in PET recycling from NIR hyperspectral images. Journal of Chemometrics. 32(1):1-14. https://doi.org/10.1002/cem.2980

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/124278

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Title: Comparison of latent variable-based and artificial intelligence methods for impurity detection in PET recycling from NIR hyperspectral images
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Mecanización y Tecnología Agraria - Departament de Mecanització i Tecnologia Agrària
Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat
Issued date:
Abstract:
[EN] In polyethylene terephthalate's (PET)'s recycling processes, separation from polyvinyl chloride (PVC) is of prior relevance due to its toxicity, which degrades the final quality of recycled PET. Moreover, the potential ...[+]
Subjects: Classification , Design of experiments , Hyperspectral images , Multivariate image analysis (MIA) , Preprocessing
Copyrigths: Reserva de todos los derechos
Source:
Journal of Chemometrics. (issn: 0886-9383 )
DOI: 10.1002/cem.2980
Publisher:
John Wiley & Sons
Publisher version: http://doi.org/10.1002/cem.2980
Thanks:
Universitat Politecnica de Valencia, Grant/Award Number: UPV-FE-16-B18
Type: Artículo

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