الفهرس 
Sign Language RecognitionOnly 14 pages are availabe for public view
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Abstract
Recent technological advancements, particularly in the fields of computer vision and machine learning, have created new opportunities for sign language recognition. These technologies aim to enable real-time sign language interpretation, breaking down communication barriers and fostering greater inclusivity for the deaf and hard-of-hearing. The development of robust sign language recognition systems has enormous potential in a variety of domains, including assistive technologies, educational tools, and human-computer interaction. These technologies aim to empower people with hearing impairments by providing them with tools for effective communication and broader societal participation. The main objective of this thesis is to develop and evaluate a real-time sign language recognition system that leverages the YOLOv5 architecture alongside attention mechanisms and various activation functions as well.