Results 21 to 30 of about 1,970 (132)

Recognition of Arabic Sign Language (ArSL) Using Recurrent Neural Networks

Journal of Intelligent Learning Systems and Applications, 2012
The objective of this paper is to introduce the use of two different recurrent neural networks in human hand gesture recognition for static images. Because neural networks are a promising tool for many human computer interaction applications, this paper focuses on the ability of neural networks to assist in Arabic Sign Language(ArSL) hand gesture ...
Raed Abu Zitar
exaly   +3 more sources

Efhamni: A Deep Learning-Based Saudi Sign Language Recognition Application [PDF]

Sensors
Deaf and hard-of-hearing people mainly communicate using sign language, which is a set of signs made using hand gestures combined with facial expressions to make meaningful and complete sentences. The problem that faces deaf and hard-of-hearing people is
Lama Al Khuzayem, Suha Shafi, Safia Aljahdali, Rawan Alkhamesie, Ohoud Alzamzami   +4 more
doaj   +2 more sources

Two-hand static and dynamic Arabic sign language recognition using keypoints and shape descriptors with attention-driven feature fusion [PDF]

PeerJ Computer Science
Sign language is a vital communication tool for individuals with hearing and speech impairments, yet Arabic Sign Language (ArSL) recognition remains challenging due to signer variability, occlusions, and limited benchmark datasets.
Zarnab Kausar, Shaheryar Najam, Mohammed Alshehri, Yahya AlQahtani, Abdulmonem Alshahrani, Ahmad Jalal, Jeongmin Park   +6 more
doaj   +3 more sources

Towards a Lightweight Arabic Sign Language Translation System. [PDF]

Sensors (Basel)
There is a pressing need to build a sign-to-text translation system to simplify communication between deaf and non-deaf people. This study investigates the building of a high-performance, lightweight sign language translation system suitable for real ...
Algabri M, Mekhtiche MA, Bencherif MA, Saeed F.   +3 more
europepmc   +2 more sources

Achieving State-of-the-art Accuracy in Arabic Sign Language Recognition with VideoMAE and Data Augmentation

Journal of Disability Research
The Arabic Sign Language (ArSL) plays a vital role in facilitating communication for deaf and hard-of-hearing individuals within Arabic-speaking communities, serving as a primary medium for social interaction, education, and access to services.
Bader Nasser Alkahtani, Naseem Alsraisri, Ali Jaber Almalki   +2 more
doaj   +2 more sources

An Intelligent Real-Time System for Sentence-Level Recognition of Continuous Saudi Sign Language Using Landmark-Based Temporal Modeling [PDF]

Sensors
A persistent challenge for Deaf and Hard-of-Hearing individuals is the communication gap between sign language users and the hearing community, particularly in regions with limited automated translation resources.
Adel BenAbdennour, Mohammed Mukhtar, Osama Almolike, Bilal A. Khawaja, Abdulmajeed M. Alenezi   +4 more
doaj   +2 more sources

Hybrid Deep Learning Models for Arabic Sign Language Recognition in Healthcare Applications

Big Data and Cognitive Computing
Deaf and hearing-impaired individuals rely on sign language, a visual communication system using hand shapes, facial expressions, and body gestures. Sign languages vary by region.
Ibtihel Mansour, Mohamed Hamroun, Sonia Lajmi, Ryma Abassi, Damien Sauveron   +4 more
doaj   +2 more sources

A Bidirectional Arabic Sign Language Framework Using Deep Learning and Fuzzy Matching Score

Mathematics
Sign language is widely used to facilitate the communication process between deaf people and their surrounding environment. Sign language, like most other languages, is considered a complex language which cannot be mastered easily.
Mogeeb A. A. Mosleh, Adel Assiri, Abdu H. Gumaei, Bader Fahad Alkhamees, Manal Al-Qahtani   +4 more
doaj   +2 more sources

Video-Based Arabic Sign Language Recognition with Mediapipe and Deep Learning Techniques [PDF]

Journal of Imaging
This paper addresses the critical communication barrier experienced by deaf and hearing-impaired individuals in the Arab world through the development of an affordable, video-based Arabic Sign Language (ArSL) recognition system.
Dana El-Rushaidat, Nour Almohammad, Raine Yeh, Kinda Fayyad   +3 more
doaj   +2 more sources

Self-supervised learning with a contrastive VideoMoCo framework for Saudi Arabic sign language recognition using 3D convolutional networks [PDF]

Scientific Reports
Saudi Arabic Sign Language (SArSL) recognition poses significant challenges due to its complex spatio-temporal structure and the scarcity of annotated datasets.
Mahmoud Rokaya, Dalia I. Hemdan, Mohammed A. Alzain, Ibrahim Gad, El-Sayed Atlam   +4 more
doaj   +2 more sources