A systematic review on hand gesture recognition techniques, challenges and applications
Background With the development of today's technology, and as humans tend to naturally
use hand gestures in their communication process to clarify their intentions, hand gesture …
use hand gestures in their communication process to clarify their intentions, hand gesture …
Quantitative survey of the state of the art in sign language recognition
O Koller - arXiv preprint arXiv:2008.09918, 2020 - arxiv.org
This work presents a meta study covering around 300 published sign language recognition
papers with over 400 experimental results. It includes most papers between the start of the …
papers with over 400 experimental results. It includes most papers between the start of the …
A comprehensive review of sign language recognition: Different types, modalities, and datasets
M Madhiarasan, PP Roy - arXiv preprint arXiv:2204.03328, 2022 - arxiv.org
A machine can understand human activities, and the meaning of signs can help overcome
the communication barriers between the inaudible and ordinary people. Sign Language …
the communication barriers between the inaudible and ordinary people. Sign Language …
Sign language recognition using deep learning on custom processed static gesture images
A Das, S Gawde, K Suratwala… - … Conference on Smart …, 2018 - ieeexplore.ieee.org
Sign Language detection by technology is an overlooked concept despite there being a
large social group which could benefit by it. There are not many technologies which help in …
large social group which could benefit by it. There are not many technologies which help in …
Retracted article: a study on Arabic sign language recognition for differently abled using advanced machine learning classifiers
M Mustafa - Journal of Ambient Intelligence and Humanized …, 2021 - Springer
This study is proposed to review the sign language recognition system based on different
classifier techniques. Mostly the Neural Network and Deep Learning-based classifiers were …
classifier techniques. Mostly the Neural Network and Deep Learning-based classifiers were …
A cross-attention BERT-based framework for continuous sign language recognition
Continuous sign language recognition (CSLR) is a challenging task involving various signal
processing techniques to infer the sequences of glosses performed by signers. Existing …
processing techniques to infer the sequences of glosses performed by signers. Existing …
Reviewing 25 years of continuous sign language recognition research: Advances, challenges, and prospects
Sign language is a form of visual communication employing hand gestures, body
movements, and facial expressions. The growing prevalence of hearing impairment has …
movements, and facial expressions. The growing prevalence of hearing impairment has …
Arabic sign language recognition with 3d convolutional neural networks
M ElBadawy, AS Elons, HA Shedeed… - 2017 Eighth …, 2017 - ieeexplore.ieee.org
Sign Language recognition is very important for communication purposes between Hearing
Impaired (HI) people and hearing ones. Arabic Sign Language Recognition field became …
Impaired (HI) people and hearing ones. Arabic Sign Language Recognition field became …
[PDF][PDF] Automatic recognition of Arabic alphabets sign language using deep learning.
RM Duwairi, ZA Halloush - International Journal of Electrical & …, 2022 - academia.edu
Technological advancements are helping people with special needs overcome many
communications' obstacles. Deep learning and computer vision models are innovative leaps …
communications' obstacles. Deep learning and computer vision models are innovative leaps …
[PDF][PDF] Semantic Deep Learning to Translate Dynamic Sign Language.
EK Elsayed, DR Fathy - International Journal of Intelligent Engineering & …, 2021 - inass.org
Dynamic Sign Language Recognition aims to recognize hand gestures of any person.
Dynamic Sign Language Recognition systems have challenges in recognizing the semantic …
Dynamic Sign Language Recognition systems have challenges in recognizing the semantic …