AIFS: an efficient face recognition method based on AI and enhanced few-shot learning.

ABSTRACT: The growing demand for real-time, adaptive facial recognition in resource-constrained environments like telemedicine, surveillance, and biometric authentication necessitates scalable AI solutions. Existing systems often falter under low-data conditions or limited computational resources. This paper introduces AIFS, an efficient and hybrid facial recognition framework that unifies traditional feature-based learning with modern few-shot deep learning under a shared Siamese architecture. The framework proposes two synergistic approaches: (1) a lightweight edge-oriented path using the Viola-Jones algorithm combined with Particle Swarm Optimization (PSO) for facial feature extraction within a Siamese network, optimized for low-power devices, and (2) a deep learning cloud-oriented path using a S

SUBMITTER: Nasralla MM 

PROVIDER: S-EPMC12775449 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature