While decade-long research has clearly demonstrated the vast potential of radio frequency
(RF) for many human sensing tasks, scaling this technology to large scenarios remained …

In recent years, radio frequency (RF) sensing has gained increasing popularity due to its
pervasiveness, low cost, non-intrusiveness, and privacy preservation. However, realizing the …

There is a growing literature demonstrating the feasibility of using Radio Frequency (RF)
signals to enable key computer vision tasks in the presence of occlusions and poor lighting …

While deep machine learning technologies are now pervasive in state-of-the-art image
recognition and natural language processing applications, only in recent years have these …

In this article, we propose a general deep learning framework for RF sensing in the IoT. We
first present the proposed framework, and then review various RF sensing techniques, deep …

Wireless propagation is conventionally considered as the enabling tool for transporting
information in digital communications. However, recent research has shown that the …

Radio-Frequency (RF) based device-free Human Activity Recognition (HAR) rises as a
promising solution for many applications. However, device-free (or contactless) sensing is …

In this paper, we propose a novel, generalizable, and scalable idea that eliminates the need
for collecting Radio Frequency (RF) measurements, when training RF sensing systems for …

Wireless sensing is an emerging technique which empowers wireless devices with
additional sensing ability, that is, the ability to sense the target location, activity, gesture, vital …

We designed and implemented a deep learning based RF signal classifier on the Field
Programmable Gate Array (FPGA) of an embedded software-defined radio platform …