FestivalNet: a deep learning architecture to classify the Indian heritage art-rangoli.
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| Title: | FestivalNet: a deep learning architecture to classify the Indian heritage art-rangoli. |
|---|---|
| Authors: | A, Sasithradevi1 (AUTHOR) sasithradevi.a@vit.ac.in, Nathan, Sabari2 (AUTHOR), Mansoor Roomi, S. Mohamed3 (AUTHOR), P, Prakash4 (AUTHOR) |
| Source: | npj Heritage Science. 12/29/2025, Vol. 13 Issue 1, p1-13. 13p. |
| Database: | Academic Search Ultimate |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: asn DbLabel: Academic Search Ultimate An: 190547478 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=190547478 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s40494-025-02229-1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 1 Titles: – TitleFull: FestivalNet: a deep learning architecture to classify the Indian heritage art-rangoli. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: A, Sasithradevi – PersonEntity: Name: NameFull: Nathan, Sabari – PersonEntity: Name: NameFull: Mansoor Roomi, S. Mohamed – PersonEntity: Name: NameFull: P, Prakash IsPartOfRelationships: – BibEntity: Dates: – D: 29 M: 12 Text: 12/29/2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20507445 Numbering: – Type: volume Value: 13 – Type: issue Value: 1 Titles: – TitleFull: npj Heritage Science Type: main |
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