The Intelligent System for Mask Detection using Deep Learning

P. Kamencay, M. Benco, R. Hudec, P. Sykora, M. Paralic
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Abstract

The main goal of the paper is to develop and design an intelligent system for automatic conditional access in critical virologic situations. The detection of proper use of face-mask, touchless temperature measurement, and counting incoming/outcoming people for single or multiple entrance doors or gates are the main objectives of this system. Originality and innovativeness of the paper are already in the idea, to create a new generation of affordable guard systems based on artificial intelligence with an emphasis on the pandemic situation in the world. In this paper, we will describe relevant works that used deep learning in security with compliance with pandemic regulations in comparison with proposed solution. The proposed technology will enable the start of a new generation of guard systems based on artificial intelligence with an emphasis on the pandemic regulations. This will create space for innovative solutions in the security of buildings, shops, factories, public transport stations, airports, etc. The implementation of this technology can bring revolutionary changes in society in actual situation and in the future.
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基于深度学习的掩码检测智能系统
本文的主要目标是开发和设计一个在关键病毒学情况下自动条件访问的智能系统。该系统的主要目标是检测口罩的正确使用,非接触式温度测量,以及对单个或多个入口或大门的进出人员进行计数。论文的原创性和创新性已经体现在理念上,即以全球疫情为重点,打造基于人工智能的新一代经济实惠的防护系统。在本文中,我们将描述在符合流行病法规的安全中使用深度学习的相关工作,并与提出的解决方案进行比较。拟议的技术将使以大流行法规为重点的基于人工智能的新一代警卫系统得以启动。这将为建筑物、商店、工厂、公共交通车站、机场等安全领域的创新解决方案创造空间。这项技术的实施可以在现实和未来给社会带来革命性的变化。
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