Enabling Two-Way Communication of Deaf Using Saudi Sign Language-Reference-Cited by-同舟云学术

Enabling Two-Way Communication of Deaf Using Saudi Sign Language

Published:2023 Issue: Volume:11 Page:135423-135434
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Faisal Mohammed¹^ORCID,Alsulaiman Mansour²^ORCID,Mekhtiche Mohamed²^ORCID,Abdelkader Bencherif Mohamed²,Algabri Mohammed³,Alrayes Tariq Bin Saleh⁴,Muhammad Ghulam²^ORCID,Mathkour Hassan⁵,Abdul Wadood²,Alohali Yousef⁵,Al-Hammadi Muneer⁶^ORCID,Altaheri Hamdi²^ORCID,Alfakih Taha⁵^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Faculty of Engineering, Kuwait College of Science and Technology (KCST), Kuwait City, Kuwait

2. Computer Engineering Department, College of Computer and Information Science, King Saud University, Riyadh, Saudi Arabia

3. Computer Science and Information Systems Department, College of Applied Sciences, AlMaarefa University, Riyadh, Saudi Arabia

4. Department of Special Education, College of Education, King Saud University, Riyadh, Saudi Arabia

5. Computer Science Department, College of Computer and Information Science, King Saud University, Riyadh, Saudi Arabia

6. Department of Civil and Environmental Engineering, Faculty of Engineering, Norwegian University of Science and Technology, Høgskoleringen, Trondheim, Norway

Funder

Targeted Research Grant Program, National Transformation Program in King Abdulaziz City for Science and Technology, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10330906.pdf?arnumber=10330906

Reference61 articles.

1. Educating Deaf Students

2. Bilingualism and Bilingual Deaf Education

3. 5. The Efficacy of Visual Input Enhancement in Teaching Deaf Learners of L2 English

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1. Establishing a multimodal dataset for Arabic Sign Language (ArSL) production;Journal of King Saud University - Computer and Information Sciences;2024-10

2. Efhamni: A Deep Learning-Based Saudi Sign Language Recognition Application;Sensors;2024-05-14