Hand gestures recognition using radar sensors for human-computer-interaction: A review
Human–Computer Interfaces (HCI) deals with the study of interface between humans and
computers. The use of radar and other RF sensors to develop HCI based on Hand Gesture …
computers. The use of radar and other RF sensors to develop HCI based on Hand Gesture …
Sign language recognition systems: A decade systematic literature review
Despite the importance of sign language recognition systems, there is a lack of a Systematic
Literature Review and a classification scheme for it. This is the first identifiable academic …
Literature Review and a classification scheme for it. This is the first identifiable academic …
RF-net: A unified meta-learning framework for RF-enabled one-shot human activity recognition
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 …
promising solution for many applications. However, device-free (or contactless) sensing is …
Deep neural networks for human activity recognition with wearable sensors: Leave-one-subject-out cross-validation for model selection
Human Activity Recognition (HAR) has been attracting significant research attention
because of the increasing availability of environmental and wearable sensors for collecting …
because of the increasing availability of environmental and wearable sensors for collecting …
Hand gesture recognition using deep feature fusion network based on wearable sensors
Hand gesture recognition is an important way for human machine interaction, and it is widely
used in many areas, such as health care, smart home, virtual reality as well as other areas …
used in many areas, such as health care, smart home, virtual reality as well as other areas …
Tinyradarnn: Combining spatial and temporal convolutional neural networks for embedded gesture recognition with short range radars
This work proposes a low-power high-accuracy embedded hand-gesture recognition
algorithm targeting battery-operated wearable devices using low-power short-range RADAR …
algorithm targeting battery-operated wearable devices using low-power short-range RADAR …
[Retracted] Hypertuned Deep Convolutional Neural Network for Sign Language Recognition
A Mannan, A Abbasi, AR Javed… - Computational …, 2022 - Wiley Online Library
Sign language plays a pivotal role in the lives of impaired people having speaking and
hearing disabilities. They can convey messages using hand gesture movements. American …
hearing disabilities. They can convey messages using hand gesture movements. American …
Indian sign language alphabet recognition system using CNN with diffGrad optimizer and stochastic pooling
India has the largest deaf population in the world and sign language is the principal medium
for such persons to share information with normal people and among themselves. Yet …
for such persons to share information with normal people and among themselves. Yet …
Detecting mid-air gestures for digit writing with radio sensors and a CNN
In this paper, we classify digits written in mid-air using hand gestures. Impulse radio
ultrawideband (IR-UWB) radar sensors are used for data acquisition, with three radar …
ultrawideband (IR-UWB) radar sensors are used for data acquisition, with three radar …
Deep-learning methods for hand-gesture recognition using ultra-wideband radar
S Skaria, A Al-Hourani, RJ Evans - IEEE Access, 2020 - ieeexplore.ieee.org
Using deep-learning techniques for analyzing radar signatures has opened new
possibilities in the field of smart-sensing, especially in the applications of hand-gesture …
possibilities in the field of smart-sensing, especially in the applications of hand-gesture …