Publicações

Federated Learning for Secure and Privacy-Preserving Facial Recognition: Advances, Challenges, and Research Directions

AuthID
P-019-V38

Author(s)

Muhammed, A

Marcos, J

Gonçalves, N

Editor(es)

Goncalves,N;Oliveira,HP;Sanchez,JA

Tipo de Documento

Proceedings Paper

Year published

2026

Publicado

in PATTERN RECOGNITION AND IMAGE ANALYSIS, IBPRIA 2025, PT I in Lecture Notes in Computer Science, ISSN: 0302-9743

Volume: 15937, Páginas: 199-213 (15)

Conference

12Th Iberian Conference on Pattern Recognition and Image Analysis-Ibpria, Date: JUN 30-JUL 03, 2025, Location: Coimbra, PORTUGAL

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Publication Identifiers

DOI: 10.1007/978-3-031-99565-1_16

SCOPUS: 2-s2.0-105013025614

Wos: WOS:001592180600016

Source Identifiers

ISSN: 0302-9743

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Federated Learning for Secure and Privacy-Preserving Facial Recognition: Advances, Challenges, and Research Directions

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Federated Learning for Secure and Privacy-Preserving Facial Recognition: Advances, Challenges, and Research Directions

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