Radar Human Activity Recognition with an Attention-Based Deep Learning Network
Radar-based human activity recognition (HAR) provides a non-contact method for many scenarios, such as human–computer interaction, smart security, and advanced surveillance with privacy protection. Feeding radar-preprocessed micro-Doppler signals into a deep learning (DL) network is a promising appr...
Main Authors: | Sha Huan, Limei Wu, Man Zhang, Zhaoyue Wang, Chao Yang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-03-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/23/6/3185 |
Similar Items
-
HHI-AttentionNet: An Enhanced Human-Human Interaction Recognition Method Based on a Lightweight Deep Learning Model with Attention Network from CSI
by: Islam Md Shafiqul, et al.
Published: (2022-08-01) -
Wearable Sensor-Based Residual Multifeature Fusion Shrinkage Networks for Human Activity Recognition
by: Fancheng Zeng, et al.
Published: (2024-01-01) -
Lightweight Multiscale Spatio-Temporal Graph Convolutional Network for Skeleton-Based Action Recognition
by: Zhiyun Zheng, et al.
Published: (2025-04-01) -
Acoustic- and Radio-Frequency-Based Human Activity Recognition
by: Masoud Mohtadifar, et al.
Published: (2022-04-01) -
Advancing human action recognition: A hybrid approach using attention-based LSTM and 3D CNN
by: El Mehdi Saoudi, et al.
Published: (2023-09-01)