A Survey of CNN and Facial Recognition Methods in the Age of COVID-19∗

Adinma Chidumije, Fatima Gowher, Ehsan Kamalinejad, Justine Mercado, Jiwanjot Soni, Jiaofei Zhong
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引用次数: 0

Abstract

The rising popularity of facial recognition technology has prompted a lot of questions about its application, reliability, safety, and legality. The ability of a machine to identify an individual and their emotions through an image with near perfect accuracy is a testament to how far Artificial intelligence (AI) models have come. This study rigorously analyzes and consolidates several reputable materials with the purposes of answering the following questions: What is facial recognition? How is data acquired? What is the machine learning process? How does the Convolution Neural Network (CNN) work? It also explores the potential obstructions such as face masks that affect the machine's accuracy, security vulnerabilities, reliability, and legal concerns of the technology.
CNN和人脸识别方法在COVID-19时代的研究*
人脸识别技术的日益普及引发了许多关于其应用、可靠性、安全性和合法性的问题。机器能够近乎完美地通过图像识别个人及其情绪,这证明了人工智能(AI)模型已经走了多远。本研究严格分析和整合了一些有信誉的材料,目的是回答以下问题:什么是面部识别?如何获取数据?什么是机器学习过程?卷积神经网络(CNN)是如何工作的?它还探讨了潜在的障碍,如口罩,影响机器的准确性,安全漏洞,可靠性和技术的法律问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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