Enhancing Facial Recognition Systems with Deep Neural Networks

Abstract

Facial recognition systems have evolved significantly over the past decade, driven by advances in deep neural networks (DNNs). This article explores how deep learning models, particularly convolutional neural networks (CNNs), are enhancing facial recognition systems by improving accuracy, speed, and robustness. We examine the architecture of deep neural networks used in facial recognition, including CNNs and deep face models, and discuss their application in various domains, such as security, healthcare, and marketing. Additionally, the article addresses challenges, ethical concerns, and future trends in the development and deployment of facial recognition technologies.