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Anglisano, Anna, Casas, Lluís, Anglisano, Marc, Queralt, Ignasi (2019) Application of Supervised Machine-Learning Methods for Attesting Provenance in Catalan Traditional Pottery Industry. Minerals, 10 (1) 8 doi:10.3390/min10010008

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Reference TypeJournal (article/letter/editorial)
TitleApplication of Supervised Machine-Learning Methods for Attesting Provenance in Catalan Traditional Pottery Industry
JournalMinerals
AuthorsAnglisano, AnnaAuthor
Casas, LluísAuthor
Anglisano, MarcAuthor
Queralt, IgnasiAuthor
Year2019 (December 20)Volume10
Issue1
PublisherMDPI AG
URL
Download URLhttps://www.mdpi.com/2075-163X/10/1/8/pdf?version=1579489599
DOIdoi:10.3390/min10010008Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID7736259Long-form Identifiermindat:1:5:7736259:9
GUID0
Full ReferenceAnglisano, Anna, Casas, Lluís, Anglisano, Marc, Queralt, Ignasi (2019) Application of Supervised Machine-Learning Methods for Attesting Provenance in Catalan Traditional Pottery Industry. Minerals, 10 (1) 8 doi:10.3390/min10010008
Plain TextAnglisano, Anna, Casas, Lluís, Anglisano, Marc, Queralt, Ignasi (2019) Application of Supervised Machine-Learning Methods for Attesting Provenance in Catalan Traditional Pottery Industry. Minerals, 10 (1) 8 doi:10.3390/min10010008
In(2019, December) Minerals Vol. 10 (1) MDPI AG

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Casas, Lluís, Anglisano, Anna, Di Febo, Roberta, Pedreño, Berta, Queralt, Ignasi (2023) Supervised Machine Learning Algorithms to Discriminate Two Similar Marble Varieties, a Case Study. Minerals, 13 (7) 861 doi:10.3390/min13070861
Casas, Lluís, Di Febo, Roberta, Boix, Carme, Egea, Albert, Vallcorba, Oriol, Queralt, Ignasi, Anglisano, Anna, Moreno, Isabel, Andino, Lorena (2021) The Colors of the Circus Mosaic from Barcino (Roman Barcelona): Characterization, Provenance, and Technology Issues. Minerals, 11 (7) 746 doi:10.3390/min11070746
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Jooshaki, Mohammad, Nad, Alona, Michaux, Simon (2021) A Systematic Review on the Application of Machine Learning in Exploiting Mineralogical Data in Mining and Mineral Industry. Minerals, 11 (8) 816 doi:10.3390/min11080816
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