Performance analysis of lung cancer detection and classification using efficientNet: a deep learning model.
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| Title: | Performance analysis of lung cancer detection and classification using efficientNet: a deep learning model. |
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| Authors: | A, Priya1, priyaanbazhagan1912@gmail.com, P, Shyamala Bharathi1, shyamalabharathip.sse@saveetha.com |
| Source: | Multimedia Tools & Applications; Jun2025, Vol. 84 Issue 21, p24273-24287, 15p |
| 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: 186341074 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Performance analysis of lung cancer detection and classification using efficientNet: a deep learning model. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22A%2C+Priya%22">A, Priya</searchLink><relatesTo>1</relatesTo>, <i>priyaanbazhagan1912@gmail.com</i><br /><searchLink fieldCode="AU" term="%22P%2C+Shyamala+Bharathi%22">P, Shyamala Bharathi</searchLink><relatesTo>1</relatesTo>, <i>shyamalabharathip.sse@saveetha.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Multimedia+Tools+%26+Applications%22">Multimedia Tools & Applications</searchLink>; Jun2025, Vol. 84 Issue 21, p24273-24287, 15p |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=186341074 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11042-024-19990-3 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 24273 Titles: – TitleFull: Performance analysis of lung cancer detection and classification using efficientNet: a deep learning model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: A, Priya – PersonEntity: Name: NameFull: P, Shyamala Bharathi IsPartOfRelationships: – BibEntity: Dates: – D: 21 M: 06 Text: Jun2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 13807501 Numbering: – Type: volume Value: 84 – Type: issue Value: 21 Titles: – TitleFull: Multimedia Tools & Applications Type: main |
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