A Hybrid CNN–LSTM Network for the Classification of Human Activities Based on Micro-Doppler Radar

A Hybrid CNN–LSTM Network for the Classification of Human Activities Based on Micro-Doppler Radar

Many deep learning (DL) models have shown exceptional promise in radar-based human activity recognition (HAR) area. For radar-based HAR, the raw data is generally converted into a 2-D spectrogram by using short-time Fourier transform (STFT). All the existing DL methods treat the spectrogram as an op...

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Bibliographic Details
Main Authors: Jianping Zhu, Haiquan Chen, Wenbin Ye
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Radar signal processing
human activity recognition
convolutional neural network
recurrent neural network
deep learning
Online Access:https://ieeexplore.ieee.org/document/8978926/

Internet

https://ieeexplore.ieee.org/document/8978926/

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