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DC Field | Value | Language |
---|---|---|
dc.contributor.author | AMEUR, Lina | - |
dc.contributor.author | MOKDAD, Fatiha (Directeur de thèse) | - |
dc.date.accessioned | 2025-03-11T08:36:46Z | - |
dc.date.available | 2025-03-11T08:36:46Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | http://dspace.ensta.edu.dz/jspui/handle/123456789/303 | - |
dc.description | Mémoire de fin d’étude du Master: Systèmes Embarqués:Alger: Ecole Nationale Supérieure des Technologie Avancées: 2024 | en_US |
dc.description.abstract | Facial recognition technology has significantly evolved over the past decade, finding applications in security, social media, and various other fields. One of the emerging and intriguing applications of this technology is kinship determina- tion, which involves determining familial relationships based on facial features. In this paper, we established the state-of-the-art understanding of these methods is essential for advancing this field and leveraging its potential for practical applications. | en_US |
dc.language.iso | en | en_US |
dc.publisher | ENSTA | en_US |
dc.subject | LBP | en_US |
dc.subject | feature selection | en_US |
dc.subject | kinship verification | en_US |
dc.subject | face analysis | en_US |
dc.subject | deep learning | en_US |
dc.subject | metric learning | en_US |
dc.subject | feature extraction | en_US |
dc.title | State of the art on facial recognition methods for determination of kinship | en_US |
dc.type | Article | en_US |
Appears in Collections: | ART- Systèmes Embarqués |
Files in This Item:
File | Description | Size | Format | |
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AMEUR_Lina_MFE_MmeMOKDAD_ MmeCHOUAF_2023-2024 - CHOUAF Seloua.pdf | Mémoire du Master | 1.32 MB | Adobe PDF | View/Open |
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