id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-102774-mtbo1tnq	Sun, Yuliang	Real-Time Radar-Based Gesture Detection and Recognition Built in an Edge-Computing Platform	2020-05-20		.txt	text/plain	6381	348	60	In this paper, a real-time signal processing frame-work based on a 60 GHz frequency-modulated continuous wave (FMCW) radar system to recognize gestures is proposed. In order to improve the robustness of the radar-based gesture recognition system, the proposed framework extracts a comprehensive hand profile, including range, Doppler, azimuth and elevation, over multiple measurement-cycles and encodes them into a feature cube. Rather than feeding the range-Doppler spectrum sequence into a deep convolutional neural network (CNN) connected with recurrent neural networks, the proposed framework takes the aforementioned feature cube as input of a shallow CNN for gesture recognition to reduce the computational complexity. [16] projected the range-Doppler-measurement-cycles into rangetime and Doppler-time to reduce the input dimension of the LSTM layer and achieved a good classification accuracy in real-time, the proposed algorithms were implemented on a personal computer with powerful computational capability.	./cache/cord-102774-mtbo1tnq.txt	./txt/cord-102774-mtbo1tnq.txt