Results 101 to 110 of about 1,970 (132)

American Sign Language Recognition Using Leap Motion Controller with Machine Learning Approach. [PDF]

Sensors (Basel), 2018
Chong TW, Lee BG.
europepmc   +1 more source

Bilingual Sign Language Recognition: A YOLOv11-Based Model for Bangla and English Alphabets. [PDF]

J Imaging
Navin N, Farid FA, Rakin RZ, Tanzim SS, Rahman M, Rahman S, Uddin J, Karim HA.   +7 more
europepmc   +1 more source

LAVRF: Sign language recognition via Lightweight Attentive VGG16 with Random Forest. [PDF]

PLoS One
Ewe ELR, Lee CP, Lim KM, Kwek LC, Alqahtani A.   +4 more
europepmc   +1 more source

Depth Perception Based on the Interaction of Binocular Disparity and Motion Parallax Cues in Three-Dimensional Space. [PDF]

Sensors (Basel)
Li S, He S, Dong Y, Dai C, Liu J, Wang Y, Shigemasu H.   +6 more
europepmc   +1 more source

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Co-design of Gesture-Based Arabic Sign Language (ArSL) Recognition

Advances in Intelligent Systems and Computing, 2021
Deaf and hard of hearing (DHH) individuals face barriers to communicating with others using sign language. Accordingly, the need for sign language translators is growing significantly. Technology plays an important role in our lives because it allows communication to be more convenient and effective, especially for DHH individuals, who desire privacy ...
Abeer Alnafjan
exaly   +3 more sources

Designing “Najeeb”: Technology-Enhanced Learning For Children With Impaired Hearing Using Arabic Sign-Language ArSL Applications

2017 International Conference on Computer and Applications (ICCA), 2017
Technology is increasingly being used to motivate learning. Deaf children in the Arab-speaking world traditionally face challenges in acquiring basic skills and encounter difficulties particular to their abilities. Their inclusion in regular schooling contexts in our education system places much responsibility for their success on the support of ...
Abeer Alnafjan
exaly   +3 more sources

Arabic Sign Language Recognition (ArSL) Approach Using Support Vector Machine

2017 27th International Conference on Computer Theory and Applications (ICCTA), 2017
Sign Language Recognition is an important method that improves communication between deaf people and normal people. In this paper, we introduce an approach that recognizes signs of alphabets of Arabic sign language. We worked on 28 signs of distinctive signs on the part of alphabetical characters of Arabic language; our experiments have applied on the ...
Mohamed Arafa Ali, Mohamed Rabie Ewis, Gamal Eid Mohamed, Heba Hamdy Ali, Hossam M. Moftah   +4 more
openaire   +1 more source

Revolutionizing Communication with Deep Learning and XAI for Enhanced Arabic Sign Language Recognition

arXiv.org
This study introduces an integrated approach to recognizing Arabic Sign Language (ArSL) using state-of-the-art deep learning models such as MobileNetV3, ResNet50, and EfficientNet-B2.
Mazen Balat, Rewaa Awaad, A. Zaky, Salah A. Aly   +3 more
semanticscholar   +1 more source

Development of an Arabic Sign Language Recognition System Utilizing Deep Convolutional Neural Network

2025 Fifth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)
The ability to recognize sign language movements, especially Arabic Sign Language (ArSL), is necessary to increase the conversation accessibility for the those who are hard of hearing or deaf.
Meenal R. Kale, Chamandeep Kaur, Indrajeet Kumar, H. S. Mahdi, Vijay N. Uprikar, Sankari V   +5 more
semanticscholar   +1 more source

Explaining Arabic Sign Language Recognition: A YOLOv11 and Transformer Hybrid Model with Grad-CAM Visualizations

2025 1st International Conference on Artificial Intelligence and Cyber Physical Systems (AICPS)
Arabic Sign Language (ArSL) recognition plays a vital role in facilitating communication between deaf communities and the hearing population in Arab countries.
Nabil Hezil, A. Bouridane, Ghania Hamdani, Oleg Y. Rogov   +3 more
semanticscholar   +1 more source