Advancements and Comparative Analysis of Real-Time Face Recognition Systems

This paper investigates diverse face recognition methodologies within centralized computer vision systems, encompassing traditional techniques, deep learning frameworks, and cloud-based solutions. It explores optimization strategies aimed at enhancing model performance and efficiency. Through rigorous evaluation and comparative analysis, the study elucidates the strengths and limitations of each approach, providing valuable insights for practitioners and researchers. The findings contribute to the advancement of face recognition technology, offering guidance for future research endeavors and practical implementations in various real-world applications.