Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …
application areas. Since multi-sensor is defined by the presence of more than one model or …
Human-machine interaction sensing technology based on hand gesture recognition: A review
L Guo, Z Lu, L Yao - IEEE Transactions on Human-Machine …, 2021 - ieeexplore.ieee.org
Human machine interaction (HMI) is an interactive way of information exchange between
human and machine. By collecting the information that can be conveyed by the person to …
human and machine. By collecting the information that can be conveyed by the person to …
Soli: Ubiquitous gesture sensing with millimeter wave radar
This paper presents Soli, a new, robust, high-resolution, low-power, miniature gesture
sensing technology for human-computer interaction based on millimeter-wave radar. We …
sensing technology for human-computer interaction based on millimeter-wave radar. We …
Autonomous vehicles that interact with pedestrians: A survey of theory and practice
A Rasouli, JK Tsotsos - IEEE transactions on intelligent …, 2019 - ieeexplore.ieee.org
One of the major challenges that autonomous cars are facing today is driving in urban
environments. To make it a reality, autonomous vehicles require the ability to communicate …
environments. To make it a reality, autonomous vehicles require the ability to communicate …
Online detection and classification of dynamic hand gestures with recurrent 3d convolutional neural network
Automatic detection and classification of dynamic hand gestures in real-world systems
intended for human computer interaction is challenging as: 1) there is a large diversity in …
intended for human computer interaction is challenging as: 1) there is a large diversity in …
MMTM: Multimodal transfer module for CNN fusion
In late fusion, each modality is processed in a separate unimodal Convolutional Neural
Network (CNN) stream and the scores of each modality are fused at the end. Due to its …
Network (CNN) stream and the scores of each modality are fused at the end. Due to its …
Multi-sensor guided hand gesture recognition for a teleoperated robot using a recurrent neural network
Touch-free guided hand gesture recognition for human-robot interactions plays an
increasingly significant role in teleoperated surgical robot systems. Indeed, despite depth …
increasingly significant role in teleoperated surgical robot systems. Indeed, despite depth …
Hand gesture recognition with 3D convolutional neural networks
Touchless hand gesture recognition systems are becoming important in automotive user
interfaces as they improve safety and comfort. Various computer vision algorithms have …
interfaces as they improve safety and comfort. Various computer vision algorithms have …
Deep learning-based sign language recognition system for static signs
A Wadhawan, P Kumar - Neural computing and applications, 2020 - Springer
Sign language for communication is efficacious for humans, and vital research is in progress
in computer vision systems. The earliest work in Indian Sign Language (ISL) recognition …
in computer vision systems. The earliest work in Indian Sign Language (ISL) recognition …
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 …