Quantum-inspired learning vector quantizers for prototype-based classification: Confidential: for personal use only—submitted to Neural Networks and Applications 5/2020.
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| Title: | Quantum-inspired learning vector quantizers for prototype-based classification: Confidential: for personal use only—submitted to Neural Networks and Applications 5/2020. |
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| Authors: | Villmann, Thomas1, thomas.villmann@hs-mittweida.de, Engelsberger, Alexander1, Ravichandran, Jensun1, Villmann, Andrea2, Kaden, Marika1 |
| Source: | Neural Computing & Applications; Jan2022, Vol. 34 Issue 1, p79-88, 10p |
| 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: 154580928 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Quantum-inspired learning vector quantizers for prototype-based classification: Confidential: for personal use only—submitted to Neural Networks and Applications 5/2020. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Villmann%2C+Thomas%22">Villmann, Thomas</searchLink><relatesTo>1</relatesTo>, <i>thomas.villmann@hs-mittweida.de</i><br /><searchLink fieldCode="AU" term="%22Engelsberger%2C+Alexander%22">Engelsberger, Alexander</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Ravichandran%2C+Jensun%22">Ravichandran, Jensun</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Villmann%2C+Andrea%22">Villmann, Andrea</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Kaden%2C+Marika%22">Kaden, Marika</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Neural+Computing+%26+Applications%22">Neural Computing & Applications</searchLink>; Jan2022, Vol. 34 Issue 1, p79-88, 10p |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=154580928 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00521-020-05517-y Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 79 Titles: – TitleFull: Quantum-inspired learning vector quantizers for prototype-based classification: Confidential: for personal use only—submitted to Neural Networks and Applications 5/2020. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Villmann, Thomas – PersonEntity: Name: NameFull: Engelsberger, Alexander – PersonEntity: Name: NameFull: Ravichandran, Jensun – PersonEntity: Name: NameFull: Villmann, Andrea – PersonEntity: Name: NameFull: Kaden, Marika IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 09410643 Numbering: – Type: volume Value: 34 – Type: issue Value: 1 Titles: – TitleFull: Neural Computing & Applications Type: main |
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