Large Class Arabic Sign Language Recognition

Zakia Saadaoui, Zakia Saadaoui, Rakia Saidi, Fethi Jarray, Fethi Jarray

2022

Abstract

Sign languages are as rich, complex and creative as spoken languages, and consist of hand movements, facial expressions and body language. Today, sign language is the language most commonly used by many deaf people and is also learned by hearing people who wish to communicate with the deaf community. Arabic sign language has been the subject of research activities to recognize signs and hand gestures using a deep learning model. A vision-based system by applying a deep neural network for letters and digits recognition based on Arabic hand signs is proposed in this paper.

Paper Citation

in Harvard Style

Saadaoui Z., Saidi R. and Jarray F. (2022). Large Class Arabic Sign Language Recognition. In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 2: KEOD; ISBN 978-989-758-614-9, SciTePress, pages 165-168. DOI: 10.5220/0011539800003335

in Bibtex Style

@conference{keod22,
author={Zakia Saadaoui and Rakia Saidi and Fethi Jarray},
title={Large Class Arabic Sign Language Recognition},
booktitle={Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 2: KEOD},
year={2022},
pages={165-168},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011539800003335},
isbn={978-989-758-614-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 2: KEOD
TI - Large Class Arabic Sign Language Recognition
SN - 978-989-758-614-9
AU - Saadaoui Z.
AU - Saidi R.
AU - Jarray F.
PY - 2022
SP - 165
EP - 168
DO - 10.5220/0011539800003335
PB - SciTePress