UAVs and birds classification using robust coordinate attention synergy residual split-attention network based on micro-Doppler signature measurement by using L …
Develo** unmanned aerial vehicles (UAVs) and birds surveillance technologies to
produce accurate descriptions and achieve high classification accuracy is critical in the field …
produce accurate descriptions and achieve high classification accuracy is critical in the field …
Improving human activity classification based on micro-doppler signatures of FMCW radar with the effect of noise
Nowadays, classifying human activities is applied in many essential fields, such as
healthcare, security monitoring, and search and rescue missions. Radar sensor-based …
healthcare, security monitoring, and search and rescue missions. Radar sensor-based …
Improving Human Activity Classification Based on Micro-Doppler Signatures Separation of FMCW Radar
NB Nguyen, TT Nguyen, MN Pham… - 2023 12th International …, 2023 - ieeexplore.ieee.org
Nowadays, Deep Convolutional Neural Networks (DCNNs) along with their outstanding
advantages, are being widely used to identify human activities based on micro-Doppler …
advantages, are being widely used to identify human activities based on micro-Doppler …
Indoor human action recognition based on millimeter-wave radar micro-doppler signature
Considering that millimeter-wave radar lacks sufficient data to support Transfer Learning
(TL) and Human Action Recognition (HAR), we propose a Heterogeneous Multi-source …
(TL) and Human Action Recognition (HAR), we propose a Heterogeneous Multi-source …
Micro-Doppler signatures based human activity classification using Dense-Inception Neural Network
Falls are the leading cause of injury and death in people over 65. Timely detection and
warning of the fall risks of humans, especially the elderly, while performing daily living …
warning of the fall risks of humans, especially the elderly, while performing daily living …
A Novel Graph Neural Network based Approach for Human Activity Recognition
Human activity recognition (HAR) is an important research area that involves detecting and
classifying human activities using various sensors. Recently, radar-based HAR systems …
classifying human activities using various sensors. Recently, radar-based HAR systems …
SRCNN: Stacked-Residual Convolutional Neural Network for Improving Human Activity Classification Based on Micro-Doppler Signatures of FMCW Radar
Current methods for daily human activity classification primarily rely on optical images from
cameras or wearable sensors. Despite their high detection reliability, camera-based …
cameras or wearable sensors. Despite their high detection reliability, camera-based …
SwinFMCW: A Joint Swin Transformer and LSTM Method for Gesture and Identity Recognition Using FMCW Radar
B Sun, Z Xu, Z Wu, S Zhang - 2022 Cross Strait Radio Science …, 2022 - ieeexplore.ieee.org
For the problem of data distortion and inadequate feature extraction in FMCW radar-based
gesture and identity multitasking recognition under smart home, smart medical, and game …
gesture and identity multitasking recognition under smart home, smart medical, and game …
Enhance micro-Doppler signatures-based human activity classification accuracy of FMCW radar using the threshold method
NB Nguyen, NP Minh, AP Huy… - Journal of Military Science …, 2024 - online.jmst.info
Nowadays, radar-based human activity classification is being widely adopted in healthcare
systems due to its benefits in terms of personal privacy compliance, non-contact sensing …
systems due to its benefits in terms of personal privacy compliance, non-contact sensing …