论文标题
面部识别系统的调查
A Survey on Face Recognition Systems
论文作者
论文摘要
事实证明，面部识别是最成功的技术之一，并影响了异质领域。由于其基于卷积的体系结构，深度学习已被证明是计算机视觉任务上最成功的。自从深度学习的出现以来，面部识别技术的准确性大大提高。在本文中，调查了一些最具影响力的面部识别系统。首先，该论文概述了一般面部识别系统。其次，调查涵盖了各种网络架构和培训损失，这些损失具有重大影响。最后，本文讨论了用于评估面部识别系统功能的各种数据库。
Face Recognition has proven to be one of the most successful technology and has impacted heterogeneous domains. Deep learning has proven to be the most successful at computer vision tasks because of its convolution-based architecture. Since the advent of deep learning, face recognition technology has had a substantial increase in its accuracy. In this paper, some of the most impactful face recognition systems were surveyed. Firstly, the paper gives an overview of a general face recognition system. Secondly, the survey covers various network architectures and training losses that have had a substantial impact. Finally, the paper talks about various databases that are used to evaluate the capabilities of a face recognition system.
