Millimeter-Wave Array Radar-Based Human Gait Recognition Using Multi-Channel Three-Dimensional Convolutional Neural Network
At present, there are two obvious problems in radar-based gait recognition. First, the traditional radar frequency band is difficult to meet the requirements of fine identification with due to its low carrier frequency and limited micro-Doppler resolution. Another significant problem is that radar s...
Main Authors: | Xinrui Jiang, Ye Zhang, Qi Yang, Bin Deng, Hongqiang Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-09-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/19/5466 |
Similar Items
-
Acceleration of FPGA Based Convolutional Neural Network for Human Activity Classification Using Millimeter-Wave Radar
by: Peng Lei, et al.
Published: (2019-01-01) -
Channel estimation based on the PSS-MUSIC for millimeter-wave MIMO systems equipped with co-prime arrays
by: Shufeng Li, et al.
Published: (2020-01-01) -
DeepGait: A Learning Deep Convolutional Representation for View-Invariant Gait Recognition Using Joint Bayesian
by: Chao Li, et al.
Published: (2017-02-01) -
Target Three-Dimensional Reconstruction From the Multi-View Radar Image Sequence
by: Yejian Zhou, et al.
Published: (2019-01-01) -
On the Effect of Training Convolution Neural Network for Millimeter-Wave Radar-Based Hand Gesture Recognition
by: Kang Zhang, et al.
Published: (2021-01-01)