新型冠状病毒口罩体温扫描系统

Sneha Bamankar, Purva Bhoir, Sharli Pednekar, G. Phadke
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引用次数: 0

摘要

在过去的两三年里,2019年冠状病毒病对整个世界产生了重大影响。在公共场合戴口罩是人们保护自己的一个重要方法。许多公共服务提供者要求用户只有在正确佩戴口罩的情况下才能使用服务。然而,只有少数研究使用图像分析来检测口罩识别。在本研究中,我们推荐一种高度精确和实用的口罩检测器Face Mask。本文提出的人脸面具检测器是一种单阶段检测器,它结合了一种新的用于检测人脸的上下文注意模块和一种特征金字塔网络,将高级语义信息与各种特征映射融合在一起。我们还提供了一种全新的跨类对象去除方法,用于拒绝和预测具有高联合交集和低置信度的对象。此外,我们研究了将Face Mask与称为MobileNet的便携式或嵌入式神经网络集成的可行性。通过利用1)非接触式温度传感,2)我们创建了一个口罩检测报警系统,以提高COVID-19室内安全。红外传感器和非接触式温度传感子系统依靠Arduino Uno,使用计算机视觉算法进行掩模识别。
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 and Body Temperature Scanning System for Covid-19
Coronavirus illness 2019 has had a major impact on the entire world over the past two to three years. One important approach for people’s protection is to wear masks in public. Furthermore, putting on a mask properly Many public service providers demand that users only utilise the service while properly wearing masks. Only a small number of studies have examined face mask identification using image analysis, nevertheless. We suggest Face Mask, a highly accurate and practical face mask detector, in this study. The suggested Face Mask is a one-stage detector that combines a novel context attention module for detecting face masks with a feature pyramid network to fuse high-level semantic information with various feature maps. We also provide a brand-new cross-class object removal method to reject and predictions with a high intersection of union and low confidence. Additionally, we investigate the viability of integrating Face Mask with a portable or embedded neural network called MobileNet. By utilising1)Contactless temperature sensing,2)we create a fack mask detection alarm system to boost COVID-19 indoor safety.Infrared sensor and contactless temperature sensing subsystems rely on Arduino Uno, while computer vision algorithms are used for mask identification.
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