Two-Stage Deep Learning Solution for Continuous Arabic Sign Language Recognition Using Word Count Prediction and Motion Images
Author:
Affiliation:
1. Department of Computer Science and Engineering, American University of Sharjah, Sharjah, United Arab Emirates
Funder
Open Access Program from the American University of Sharjah
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/ielx7/6287639/10005208/10315111.pdf?arnumber=10315111
Reference31 articles.
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2. Towards Hybrid Multimodal Manual and Non-Manual Arabic Sign Language Recognition: mArSL Database and Pilot Study
3. Intra-linguistic and extra-linguistic annotation tool for the “Jumla Dataset” in Qatari sign language
4. SignsWorld Atlas; a benchmark Arabic Sign Language database
5. Continuous Indian Sign Language Gesture Recognition and Sentence Formation
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1. Efficient YOLO-Based Deep Learning Model for Arabic Sign Language Recognition;Journal of Disability Research;2024-05-07
2. Sign Language Recognition: A Comprehensive Review of Traditional and Deep Learning Approaches, Datasets, and Challenges;IEEE Access;2024
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