Voice pathology identification system using a deep learning approach based on unique feature selection sets.
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| Title: | Voice pathology identification system using a deep learning approach based on unique feature selection sets. |
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| Authors: | Abdulmajeed, Nuha Qais1, Al‐Khateeb, Belal1, Mohammed, Mazin Abed1, mazinalshujeary@uoanbar.edu.iq |
| Source: | Expert Systems; Jan2025, Vol. 42 Issue 1, p1-25, 25p |
| 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: 181701490 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=aci&AN=181701490 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/exsy.13327 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 25 StartPage: 1 Titles: – TitleFull: Voice pathology identification system using a deep learning approach based on unique feature selection sets. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Abdulmajeed, Nuha Qais – PersonEntity: Name: NameFull: Al‐Khateeb, Belal – PersonEntity: Name: NameFull: Mohammed, Mazin Abed IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 02664720 Numbering: – Type: volume Value: 42 – Type: issue Value: 1 Titles: – TitleFull: Expert Systems Type: main |
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