[HTML][HTML] Machine learning methods for sign language recognition: A critical review and analysis

IA Adeyanju, OO Bello, MA Adegboye - Intelligent Systems with …, 2021 - Elsevier
Sign language is an essential tool to bridge the communication gap between normal and
hearing-impaired people. However, the diversity of over 7000 present-day sign languages …

Hand gesture recognition with focus on leap motion: An overview, real world challenges and future directions

NM Bhiri, S Ameur, I Alouani, MA Mahjoub… - Expert Systems with …, 2023 - Elsevier
In the recent years, a steady growth of Hand Gesture Recognition (HGR) based applications
has been observed. Thus, significant progress has been made in the field of hand detection …

Spatial–temporal feature-based End-to-end Fourier network for 3D sign language recognition

SB Abdullahi, K Chamnongthai… - Expert Systems with …, 2024 - Elsevier
Most dynamic sign word misclassifications are caused by redundant spatial–temporal (SPT)
feature pruning that lacks language semantic and temporal dependencies. SPT feature …

A novel hybrid bidirectional unidirectional LSTM network for dynamic hand gesture recognition with leap motion

S Ameur, AB Khalifa, MS Bouhlel - Entertainment Computing, 2020 - Elsevier
Due to the recent development of machine learning and sensor innovations, hand gesture
recognition systems become promising for the digital entertainment field. In this paper, we …

A comparative review on applications of different sensors for sign language recognition

MS Amin, STH Rizvi, MM Hossain - Journal of Imaging, 2022 - mdpi.com
Sign language recognition is challenging due to the lack of communication between normal
and affected people. Many social and physiological impacts are created due to speaking or …

American sign language words recognition of skeletal videos using processed video driven multi-stacked deep LSTM

SB Abdullahi, K Chamnongthai - Sensors, 2022 - mdpi.com
Complex hand gesture interactions among dynamic sign words may lead to
misclassification, which affects the recognition accuracy of the ubiquitous sign language …

Arabic sign language recognition using Ada-Boosting based on a leap motion controller

B Hisham, A Hamouda - International Journal of Information Technology, 2021 - Springer
Abstract According to the World Health Organization (WHO), 466 million people are suffering
from hearing loss, ie, 5% of the world population, of which 432 million (93%) are adults and …

Dynamic hand gesture recognition based on a leap motion controller and two-layer bidirectional recurrent neural network

L Yang, J Chen, W Zhu - Sensors, 2020 - mdpi.com
Dynamic hand gesture recognition is one of the most significant tools for human–computer
interaction. In order to improve the accuracy of the dynamic hand gesture recognition, in this …

Crack type analysis and damage evaluation of BFRP-repaired pre-damaged concrete cylinders using acoustic emission technique

G Ma, C Wu - Construction and Building Materials, 2023 - Elsevier
Fiber-reinforced polymer (FRP) composites have been widely used in the retrofitting of
concrete columns after earthquakes. However, FRP composites prevent traditional field …

A real time Arabic sign language alphabets (ArSLA) recognition model using deep learning architecture

Z Alsaadi, E Alshamani, M Alrehaili, AAD Alrashdi… - Computers, 2022 - mdpi.com
Currently, treating sign language issues and producing high quality solutions has attracted
researchers and practitioners' attention due to the considerable prevalence of hearing …