Open Access

ARTICLE

Enhancing Communication Accessibility: UrSL-CNN Approach to Urdu Sign Language Translation for Hearing-Impaired Individuals

Khushal Das¹, Fazeel Abid², Jawad Rasheed^3,4,*, Kamlish⁵, Tunc Asuroglu^6,*, Shtwai Alsubai⁷, Safeeullah Soomro⁸

1 Department of Computer Engineering, Modeling Electronics and Systems Engineering, University of Calabria, Rende Cosenza, 87036, Italy
2 Department of Information Systems, University of Management and Technology, Lahore, 54770, Pakistan
3 Department of Computer Engineering, Istanbul Sabahattin Zaim University, Istanbul, 34303, Turkey
4 Department of Software Engineering, Istanbul Nisantasi University, Istanbul, 34398, Turkey
5 Department of Computer Science, COMSATS University Islamabad, Lahore Campus, Lahore, 54700, Pakistan
6 Faculty of Medicine and Health Technology, Tampere University, Tampere, 33720, Finland
7 Department of Computer Science, College of Computer Engineering and Sciences in Al-Kharj, Prince Sattam Bin Abdulaziz University, P.O. Box 151, Al-Kharj, 11942, Saudi Arabia
8 Second Department of Computer Science, College of Engineering and Computing, George Mason University, Fairfax, VA 4418, USA

* Corresponding Authors: Jawad Rasheed. Email: ; Tunc Asuroglu. Email: