Binary and Ternary Classifiers to Detect COVID-19 Patients Using Chest X-ray Images: An Efficient Layered CNN Approach.
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| Title: | Binary and Ternary Classifiers to Detect COVID-19 Patients Using Chest X-ray Images: An Efficient Layered CNN Approach. |
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| Authors: | Mittal, Mamta1, Chauhan, Nitin Kumar2, Ghansiyal, Adrija3, Hemanth, D. Jude4, judehemanth@karunya.edu |
| Source: | New Generation Computing; Nov2024, Vol. 42 Issue 4, p715-737, 23p |
| 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: 180456576 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00354-024-00254-5 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 715 Titles: – TitleFull: Binary and Ternary Classifiers to Detect COVID-19 Patients Using Chest X-ray Images: An Efficient Layered CNN Approach. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mittal, Mamta – PersonEntity: Name: NameFull: Chauhan, Nitin Kumar – PersonEntity: Name: NameFull: Ghansiyal, Adrija – PersonEntity: Name: NameFull: Hemanth, D. Jude IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 02883635 Numbering: – Type: volume Value: 42 – Type: issue Value: 4 Titles: – TitleFull: New Generation Computing Type: main |
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