An optimized hybrid framework for car theft detection: comparative insights from deep transfer learning and feature-based machine learning.
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| Title: | An optimized hybrid framework for car theft detection: comparative insights from deep transfer learning and feature-based machine learning. |
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| Authors: | Jebraeily, Yashar1, Sharafi, Yousef1, y.sharafi@kntu.ac.ir, Teshnehlab, Mohammad1, Ramezanloo, Nastaran Ahmadi2 |
| Source: | Artificial Intelligence Review; Feb2026, Vol. 59 Issue 2, p1-46, 46p |
| 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: 191000876 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10462-025-11480-8 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 46 StartPage: 1 Titles: – TitleFull: An optimized hybrid framework for car theft detection: comparative insights from deep transfer learning and feature-based machine learning. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jebraeily, Yashar – PersonEntity: Name: NameFull: Sharafi, Yousef – PersonEntity: Name: NameFull: Teshnehlab, Mohammad – PersonEntity: Name: NameFull: Ramezanloo, Nastaran Ahmadi IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 02692821 Numbering: – Type: volume Value: 59 – Type: issue Value: 2 Titles: – TitleFull: Artificial Intelligence Review Type: main |
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