Fluorescence Spectroscopy and a Convolutional Neural Network for High-Accuracy Japanese Green Tea Or...
Fluorescence Spectroscopy and a Convolutional Neural Network for High-Accuracy Japanese Green Tea Origin Identification
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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This study aims to develop a system combining fluorescence spectroscopy and machine learning through a convolutional neural network (CNN) to identify the origins of various Japanese green teas (Sayama tea, Kakegawa tea, Yame tea, and Chiran tea). Although food origin labeling is important for ensuring consumer quality and safety, ac-curate identifi...
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Fluorescence Spectroscopy and a Convolutional Neural Network for High-Accuracy Japanese Green Tea Origin Identification
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TN_cdi_doaj_primary_oai_doaj_org_article_cae8a41c35cb45df917e184b9267c413
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_cae8a41c35cb45df917e184b9267c413
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ISSN
2624-7402
E-ISSN
2624-7402
DOI
10.3390/agriengineering7040095
