Generative adversarial networks (GANs) have recently been proposed for the synthesis of
RF micro-Doppler signatures to address the issue of low sample support and enable the …

This paper presents a comprehensive dataset intended to evaluate passive Human Activity
Recognition (HAR) and localization techniques with measurements obtained from …

Human has an unique gait and prior works show increasing potentials in using WiFi signals
to capture the unique signature of individuals' gait. However, existing WiFi-based human …

In recent years, deep convolutional neural networks (DCNNs) have demonstrated the
prominent performance in the radar-based human activity recognition. However, collecting …

Radio-frequency-based noncooperative monitoring of humans has numerous applications
ranging from law enforcement to ubiquitous sensing applications such as ambient assisted …

The classification of human activity using radar has gained considerable attention in recent
years because of the radar sensor's resistance to harsh settings. However, when using …

Under the outbreak of the COVID-19 pandemic, respiration state monitoring plays an
important role in assisting respiratory disease diagnosis and treatment. Thanks to the …

Continuous and unobtrusive monitoring of daily human activities in homes can potentially
improve the quality of life and prolong independent living for the elderly and people with …

This work introduces an attention mechanism that can be integrated into any standard
convolution neural network to improve model sensitivity and prediction accuracy with …

Micro-Doppler signatures contain considerable information about target dynamics. However,
the radar sensing systems are easily affected by noisy surroundings, resulting in …