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Deep learning for sign language recognition: Current techniques, benchmarks, and open issues
People with hearing impairments are found worldwide; therefore, the development of
effective local level sign language recognition (SLR) tools is essential. We conducted a …
effective local level sign language recognition (SLR) tools is essential. We conducted a …
RETRACTED ARTICLE: Machine learning based sign language recognition: a review and its research frontier
R Elakkiya - Journal of Ambient Intelligence and Humanized …, 2021 - Springer
In the recent past, research in the field of automatic sign language recognition using
machine learning methods have demonstrated remarkable success and made momentous …
machine learning methods have demonstrated remarkable success and made momentous …
Pose-guided matching based on deep learning for assessing quality of action on rehabilitation training
Y Qiu, J Wang, Z **, H Chen, M Zhang… - … Signal Processing and …, 2022 - Elsevier
The application of pose assessment on rehabilitation training has gradually received
attention in recent years. However, current evaluation indicators of these methods are mostly …
attention in recent years. However, current evaluation indicators of these methods are mostly …
A multimodal framework for sensor based sign language recognition
In this paper, we propose a novel multimodal framework for isolated Sign Language
Recognition (SLR) using sensor devices. Microsoft Kinect and Leap motion sensors are …
Recognition (SLR) using sensor devices. Microsoft Kinect and Leap motion sensors are …
Design of hand gesture recognition system for human-computer interaction
TH Tsai, CC Huang, KL Zhang - Multimedia tools and applications, 2020 - Springer
Human-Computer interaction (HCI) with gesture recognition is designed to recognize a
number of meaningful human expressions, and has become a valuable and intuitive …
number of meaningful human expressions, and has become a valuable and intuitive …
[HTML][HTML] Recent progress in sensing and computing techniques for human activity recognition and motion analysis
The recent scientific and technical advances in Internet of Things (IoT) based pervasive
sensing and computing have created opportunities for the continuous monitoring of human …
sensing and computing have created opportunities for the continuous monitoring of human …
Hand gesture recognition using machine learning and infrared information: a systematic literature review
Currently, gesture recognition is like a problem of feature extraction and pattern recognition,
in which a movement is labeling as belonging to a given class. A gesture recognition …
in which a movement is labeling as belonging to a given class. A gesture recognition …
Hand gesture recognition using a radar echo I–Q plot and a convolutional neural network
We propose a hand gesture recognition technique using a convolutional neural network
applied to radar echo in-phase/quadrature (I/Q) plot trajectories. The proposed technique is …
applied to radar echo in-phase/quadrature (I/Q) plot trajectories. The proposed technique is …
Hand tracking and gesture recognition by multiple contactless sensors: A survey
Hand tracking and gesture recognition are fundamental in a multitude of applications.
Various sensors have been used for this purpose, however, all monocular vision systems …
Various sensors have been used for this purpose, however, all monocular vision systems …
Chronological pattern indexing: An efficient feature extraction method for hand gesture recognition with leap motion
Abstract Recently, Hand-Gesture-Recognition (HGR) systems has appreciably change the
way of interaction between humans and computers thanks to advanced sensor technologies …
way of interaction between humans and computers thanks to advanced sensor technologies …