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dc.contributor.authorTorre Ordás, Jorge
dc.contributor.authorBarroso Solares, Suset 
dc.contributor.authorRodríguez Pérez, Miguel Ángel 
dc.contributor.authorPinto Sanz, Javier 
dc.date.accessioned2024-02-09T08:40:39Z
dc.date.available2024-02-09T08:40:39Z
dc.date.issued2024
dc.identifier.citationPolymer, 2024, vol. 291, 126597es
dc.identifier.issn0032-3861es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/66062
dc.descriptionProducción Científicaes
dc.description.abstractThe structural characterization is an essential task in the study of porous materials. To achieve reliable results, it requires to evaluate images with hundreds of pores. Current methods require large time amounts and are subjected to human errors and subjectivity. A completely automatic tool would not only speed up the process but also enhance its reliability and reproducibility. Therefore, the main objective of this article is the study of a deep-learning-based technique for the structural characterization of porous materials, through the use of a convolutional neural network. Several fine-tuned Mask R–CNN models are evaluated using different training configurations in four separate datasets each composed of numerous SEM images of diverse polymeric porous materials: closed-pore extruded polystyrene (XPS), polyurethane (PU), and poly(methyl methacrylate) (PMMA), and open-pore PU. Results prove the tool capable of providing very accurate results, equivalent to those achieved by time-consuming manual methods, in a matter of seconds.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectPolimeros y polimerizaciónes
dc.subject.classificationDeep learninges
dc.subject.classificationMask R–CNNes
dc.subject.classificationAutomatices
dc.subject.classificationAprendizaje profundoes
dc.subject.classificationAutomáticoes
dc.subject.classificationMáscara R-CNNes
dc.titleOn the use of neural networks for the structural characterization of polymeric porous materialses
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2024 The Authorses
dc.identifier.doi10.1016/j.polymer.2023.126597es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0032386123009278?via%3Dihubes
dc.identifier.publicationfirstpage126597es
dc.identifier.publicationtitlePolymeres
dc.identifier.publicationvolume291es
dc.peerreviewedSIes
dc.description.projectMCIN/AEI/10.13039/501100011033 and the EU NextGenerationEU/PRTR program (PLEC2021-007705)es
dc.description.projectJunta de Castilla y León y el programa EU-FEDER (CLU-2019-04)es
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones
dc.subject.unesco2301.15 Análisis de Polímeroses


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