CubeLearn: End-to-End Learning for Human Motion Recognition From Raw mmWave Radar Signals
Author:
Affiliation:
1. Department of Computer Science, University of Oxford, Oxford, U.K.
2. Department of Informatics, University of Edinburgh, Edinburgh, U.K
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/6488907/10142029/10018429.pdf?arnumber=10018429
Reference42 articles.
1. An End-to-End Network for Continuous Human Motion Recognition via Radar Radios
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3. Using an End-to-End Convolutional Network on Radar Signal for Human Activity Classification
4. Spectrum-based single-snapshot super-resolution direction-of-arrival estimation using deep learning;gall;Proc IEEE German Microw Conf (GeMiC),2020
5. Gesture recognition with a low power FMCW radar and a deep convolutional neural network
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