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

Khushal Das1, Fazeel Abid2, Jawad Rasheed3,4,*, Kamlish5, Tunc Asuroglu6,*, 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: email; Tunc Asuroglu. Email: email

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