VitNas: a deep learning model for efficient identification of medicinal plants using real-world datasets.
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| Title: | VitNas: a deep learning model for efficient identification of medicinal plants using real-world datasets. |
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| Authors: | Anwar, Zeba1, zanwar1@jmi.ac.in, Masood, Sarfaraz1, smasood@jmi.ac.in |
| Source: | Multimedia Tools & Applications; Nov2025, Vol. 84 Issue 38, p47127-47153, 27p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 190277856 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: VitNas: a deep learning model for efficient identification of medicinal plants using real-world datasets. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Anwar%2C+Zeba%22">Anwar, Zeba</searchLink><relatesTo>1</relatesTo>, <i>zanwar1@jmi.ac.in</i><br /><searchLink fieldCode="AU" term="%22Masood%2C+Sarfaraz%22">Masood, Sarfaraz</searchLink><relatesTo>1</relatesTo>, <i>smasood@jmi.ac.in</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Multimedia+Tools+%26+Applications%22">Multimedia Tools & Applications</searchLink>; Nov2025, Vol. 84 Issue 38, p47127-47153, 27p |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=190277856 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11042-025-21013-8 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 27 StartPage: 47127 Titles: – TitleFull: VitNas: a deep learning model for efficient identification of medicinal plants using real-world datasets. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Anwar, Zeba – PersonEntity: Name: NameFull: Masood, Sarfaraz IsPartOfRelationships: – BibEntity: Dates: – D: 27 M: 11 Text: Nov2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 13807501 Numbering: – Type: volume Value: 84 – Type: issue Value: 38 Titles: – TitleFull: Multimedia Tools & Applications Type: main |
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