Radar and RGB-depth sensors for fall detection: A review
This paper reviews recent works in the literature on the use of systems based on radar and
RGB-Depth (RGB-D) sensors for fall detection, and discusses outstanding research …
RGB-Depth (RGB-D) sensors for fall detection, and discusses outstanding research …
Learning-by-examples techniques as applied to electromagnetics
There is a wide number of problems in electromagnetic (EM) engineering that require a real-
time response or in which the input–output relationship is not a-priori known or cannot be …
time response or in which the input–output relationship is not a-priori known or cannot be …
Deep convolutional autoencoder for radar-based classification of similar aided and unaided human activities
MS Seyfioğlu, AM Özbayoğlu… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Radar-based activity recognition is a problem that has been of great interest due to
applications such as border control and security, pedestrian identification for automotive …
applications such as border control and security, pedestrian identification for automotive …
Human detection and activity classification based on micro-Doppler signatures using deep convolutional neural networks
We propose the use of deep convolutional neural networks (DCNNs) for human detection
and activity classification based on Doppler radar. Previously, proposed schemes for these …
and activity classification based on Doppler radar. Previously, proposed schemes for these …
Toward unobtrusive in-home gait analysis based on radar micro-Doppler signatures
Objective: In this paper, we demonstrate the applicability of radar for gait classification with
application to home security, medical diagnosis, rehabilitation, and assisted living. Aiming at …
application to home security, medical diagnosis, rehabilitation, and assisted living. Aiming at …
Human target detection, tracking, and classification using 24-GHz FMCW radar
C Will, P Vaishnav, A Chakraborty… - IEEE Sensors …, 2019 - ieeexplore.ieee.org
This paper presents a millimeter-wave radar in the 24-GHz ISM band for detection, tracking,
and classification of human targets. Linear frequency modulation of the transmit signal and …
and classification of human targets. Linear frequency modulation of the transmit signal and …
American sign language recognition using rf sensing
Many technologies for human-computer interaction have been designed for hearing
individuals and depend upon vocalized speech, precluding users of American Sign …
individuals and depend upon vocalized speech, precluding users of American Sign …
Classification of unarmed/armed personnel using the NetRAD multistatic radar for micro-Doppler and singular value decomposition features
In this letter, we present the use of experimental human micro-Doppler signature data
gathered by a multistatic radar system to discriminate between unarmed and potentially …
gathered by a multistatic radar system to discriminate between unarmed and potentially …
SleepSense: A noncontact and cost-effective sleep monitoring system
Quality of sleep is an important indicator of health and well being. Recent developments in
the field of in-home sleep monitoring have the potential to enhance a person's sleeping …
the field of in-home sleep monitoring have the potential to enhance a person's sleeping …
Deep neural network initialization methods for micro-Doppler classification with low training sample support
MS Seyfioğlu, SZ Gürbüz - IEEE Geoscience and Remote …, 2017 - ieeexplore.ieee.org
Deep neural networks (DNNs) require large-scale labeled data sets to prevent overfitting
while having good generalization. In radar applications, however, acquiring a measured …
while having good generalization. In radar applications, however, acquiring a measured …