Multi-scale convolutional and temporal modeling for robust face recognition: Introducing ScaleSyncNet

doi:10.1016/j.rineng.2026.109838

Multi-scale convolutional and temporal modeling for robust face recognition: Introducing ScaleSyncNet

2026-02-28

0

OA

AI

Shahad Thamear Abd Al-Latief

Y

Yasir Hussein Shakir

E

Eshaq Aziz Awadh AL Mandhari

F

Fahad Taha AL‐Dhief *

DOI：10.1016/j.rineng.2026.109838

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Abstract

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• A novel deep learning model, ScaleSyncNet, is proposed for a robust face recognition system. • A new algorithm extracts the most discriminative features for reliable face representation. • The proposed model achieves high recognition accuracy with low computational complexity. • Experimental results show 100 % recognition accuracy with a processing time of 254 ms.

Keywords:

Face recognition

Linear Discriminant Analysis

Deep learning

ScaleSyncNet

Multi-scale convolutional and temporal modeling for robust face recognition: Introducing ScaleSyncNet

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