Continuous Human Activity Recognition With Distributed Radar Sensor Networks and CNN–RNN Architectures
Author:
Affiliation:
1. Department of Microelectronics, Delft University of Technology, Delft, The Netherlands
Funder
Dutch Research Council NWO under project RAD-ART, Radar-aware Activity Recognition with Innovative Temporal Networks
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/9633014/09825631.pdf?arnumber=9825631
Reference83 articles.
1. Personnel Recognition and Gait Classification Based on Multistatic Micro-Doppler Signatures Using Deep Convolutional Neural Networks
2. Multiple target tracking and human activity recognition based on the IR-UWB radar sensor networks;zhu,2021
3. End-to-End Mandarin Speech Recognition Combining CNN and BLSTM
4. End-to-End Low-Resource Speech Recognition with a Deep CNN-LSTM Encoder
5. Multi-View CNN-LSTM Architecture for Radar-Based Human Activity Recognition
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