Sign language recognition: A deep survey

R Rastgoo, K Kiani, S Escalera - Expert Systems with Applications, 2021 - Elsevier
Sign language, as a different form of the communication language, is important to large
groups of people in society. There are different signs in each sign language with variability …

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 …

A survey of deep neural network architectures and their applications

W Liu, Z Wang, X Liu, N Zeng, Y Liu, FE Alsaadi - Neurocomputing, 2017 - Elsevier
Since the proposal of a fast learning algorithm for deep belief networks in 2006, the deep
learning techniques have drawn ever-increasing research interests because of their …

Video-based sign language recognition without temporal segmentation

J Huang, W Zhou, Q Zhang, H Li, W Li - Proceedings of the AAAI …, 2018 - ojs.aaai.org
Millions of hearing impaired people around the world routinely use some variants of sign
languages to communicate, thus the automatic translation of a sign language is meaningful …

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 …

Deep learning-based approach for sign language gesture recognition with efficient hand gesture representation

M Al-Hammadi, G Muhammad, W Abdul… - Ieee …, 2020 - ieeexplore.ieee.org
Hand gesture recognition is an attractive research field with a wide range of applications,
including video games and telesurgery techniques. Another important application of hand …

Signbert+: Hand-model-aware self-supervised pre-training for sign language understanding

H Hu, W Zhao, W Zhou, H Li - IEEE Transactions on Pattern …, 2023 - ieeexplore.ieee.org
Hand gesture serves as a crucial role during the expression of sign language. Current deep
learning based methods for sign language understanding (SLU) are prone to over-fitting due …

Sign language recognition using 3d convolutional neural networks

J Huang, W Zhou, H Li, W Li - 2015 IEEE international …, 2015 - ieeexplore.ieee.org
Sign Language Recognition (SLR) targets on interpreting the sign language into text or
speech, so as to facilitate the communication between deaf-mute people and ordinary …

Attention-based 3D-CNNs for large-vocabulary sign language recognition

J Huang, W Zhou, H Li, W Li - IEEE Transactions on Circuits …, 2018 - ieeexplore.ieee.org
Sign language recognition (SLR) is an important and challenging research topic in the
multimedia field. Conventional techniques for SLR rely on hand-crafted features, which …

SignBERT: Pre-training of hand-model-aware representation for sign language recognition

H Hu, W Zhao, W Zhou, Y Wang… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
Hand gesture serves as a critical role in sign language. Current deep-learning-based sign
language recognition (SLR) methods may suffer insufficient interpretability and overfitting …