面罩识别在KYC生成从现场照片检测方法

Debalina Barua, Mumtahina Ahsan, Moumita Khandaker, H. M. Z. Amin, Md Humaion Kabir Mehedi, Annajiat Alim Rasel
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摘要

Covid-19大流行后的世界使人类进入了过渡频率。在这个过渡时期,世界需要为自己提供急需的技术和服务。现在需要时间来建立一个与我们共同面临的危机相适应的制度,以确保一个无风险的安全环境。为了提供安全,已经制定了新的法规和措施,其中包括定期佩戴口罩。有必要在有助于减少病毒传播的公共场所严格执行这一新规定。沿着掩模,掩模探测系统齐头并进,发挥着至关重要的作用。在官方图像记录部门,掩码检测是确保人员身份的一项要求。这种监视方法使警报系统能够在拍摄任何需要明确照片身份的文件时摘下面具。在本文中,我们简要讨论了使用深度学习算法捕获照片时面罩检测系统的这种方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Face mask recognition during KYC generation from a live photo detection methodology
Post Pandemic world of Covid-19 has set human race to a transitioned frequency. Through this transitional period the world needs to serve itself with much needed technology and services. The need of time is now to build the system compatible to the crisis we face together that ensures a risk-free safe environment. New regulations and measures have been established in order to provide safety that includes regular wear of face mask. It is necessary to strictly execute this new rule in public places that helps reducing the spread of virus. Along the mask, a mask detector system comes hand in hand playing a vital role. On official image recording sectors, the mask detection is a requirement to ensure the identity of a personnel. This surveillance method enables the alert system to remove the mask while taking any photograph for documentation that demands clear photographic identity. In this paper, we have briefly discussed this approach of face mask detection system while capturing a photo using deep learning algorithms.
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