Deep learning for sign language recognition: Current techniques, benchmarks, and open issues

M Al-Qurishi, T Khalid, R Souissi - IEEE Access, 2021 - ieeexplore.ieee.org
People with hearing impairments are found worldwide; therefore, the development of
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RETRACTED ARTICLE: Machine learning based sign language recognition: a review and its research frontier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 …

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 …

A multimodal framework for sensor based sign language recognition

P Kumar, H Gauba, PP Roy, DP Dogra - Neurocomputing, 2017 - Elsevier
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 …

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 …

[HTML][HTML] Recent progress in sensing and computing techniques for human activity recognition and motion analysis

Z Meng, M Zhang, C Guo, Q Fan, H Zhang, N Gao… - Electronics, 2020 - mdpi.com
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 …

Hand gesture recognition using machine learning and infrared information: a systematic literature review

RE Nogales, ME Benalcázar - International Journal of Machine Learning …, 2021 - Springer
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 …

Hand gesture recognition using a radar echo I–Q plot and a convolutional neural network

T Sakamoto, X Gao, E Yavari, A Rahman… - IEEE sensors …, 2018 - ieeexplore.ieee.org
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 …

Hand tracking and gesture recognition by multiple contactless sensors: A survey

E Theodoridou, L Cinque, F Mignosi… - … on Human-Machine …, 2022 - ieeexplore.ieee.org
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 …

Chronological pattern indexing: An efficient feature extraction method for hand gesture recognition with leap motion

S Ameur, AB Khalifa, MS Bouhlel - Journal of Visual Communication and …, 2020 - Elsevier
Abstract Recently, Hand-Gesture-Recognition (HGR) systems has appreciably change the
way of interaction between humans and computers thanks to advanced sensor technologies …