Deep Learning to Authenticate Traditional Handloom Textile
Deep Learning to Authenticate Traditional Handloom Textile
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Publisher
Basel: MDPI AG
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Language
English
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Publisher
Basel: MDPI AG
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Scope and Contents
Contents
Handloom textile products play an essential role in both the financial and cultural landscape of natives, necessitating accurate and efficient methods for authenticating against replicated powerloom textiles for the protection of heritage and indigenous weavers’ economic viability. This paper presents a new approach to the automated identification...
Alternative Titles
Full title
Deep Learning to Authenticate Traditional Handloom Textile
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_87555391e069451aa1f2d617daabfe7b
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_87555391e069451aa1f2d617daabfe7b
Other Identifiers
ISSN
2078-2489
E-ISSN
2078-2489
DOI
10.3390/info15080465
