id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-225826-bwghyhqx	Jiang, Zheng	Combining Visible Light and Infrared Imaging for Efficient Detection of Respiratory Infections such as COVID-19 on Portable Device	2020-04-15		.txt	text/plain	4812	276	56	In this work, we perform the health screening through the combination of the RGB and thermal videos obtained from the dual-mode camera and deep learning architecture.We first accomplish a respiratory data capture technique for people wearing masks by using face recognition. In this study, we develop a portable and intelligent health screening device that uses thermal imaging to extract respiration data from masked people which is then used to do the health screening classification via deep learning architecture. After extracting breathing data from the video obtained from the thermal camera, a deep learning neural network is performed to work on the classification between healthy and abnormal respiration conditions. First, we combine the face recognition technology with dual-mode imaging to accomplish a respiratory data extraction method for people wearing masks, which is quite essential for current situation. Finally, we use a bidirectional GRU neural network with attention mechanism (BiGRU-AT) model to work on the classification task with the input respiration data.	./cache/cord-225826-bwghyhqx.txt	./txt/cord-225826-bwghyhqx.txt