IR-ST: A Lightweight Transformer Network for Human Fall Detection Based on FMCW Radar
Author:
Affiliation:
1. School of Information Science and Engineering, Zhejiang Sci-Tech University, Hangzhou, China
Funder
Zhejiang Science Technology Department Public Service Technology Research Project
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/10286142/10254502.pdf?arnumber=10254502
Reference27 articles.
1. Recurrent attention network using spatial-temporal relations for action recognition
2. A Multi-Domain Fusion Human Motion Recognition Method Based on Lightweight Network
3. A posture recognition based fall detection system using a 24 GHz CMOS FMCW radar SoC;liang;IEEE MTT-S Int Microw Symp Dig,2021
4. Human motion recognition exploiting radar with stacked recurrent neural network
5. Contactless Fall Detection Using Time-Frequency Analysis and Convolutional Neural Networks
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1. Fall Detection of the Elderly Using Denoising LSTM-Based Convolutional Variant Autoencoder;IEEE Sensors Journal;2024-06-01
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