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Interactive Hand Gesture Recognition With Audio Response
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Author(s): P. Jeyanthi (Sathyabama Institute of Science and Technology, India), Abdul Ajees I. (Sathyabama Institute of Science and Technology, India), Abel Priya Kumar (Sathyabama Institute of Science and Technology, India), Vikash Ajin P. (Sathyabama Institute of Science and Technology, India), S. Revathy (Sathyabama Institute of Science and Technology, India)and Mary Gladence L. (Sathyabama Institute of Science and Technology, India)
Copyright: 2025
Pages: 18
Source title:
Multidisciplinary Applications of AI and Quantum Networking
Source Author(s)/Editor(s): Christo Ananth (Samarkand State University, Uzbekistan), Osamah Ibrahim Khalaf (Al-Nahrain University, Iraq)and Jose Anand (KCG College of Technology, India)
DOI: 10.4018/979-8-3693-9336-9.ch013
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Abstract
This research introduces a comprehensive sign language recognition system designed to address challenges faced by individuals seeking to learn sign language, particularly those with limited access to interactive and varied learning resources. Leveraging machine learning and computer vision technologies, the system integrates advanced hand landmark detection, dataset creation, model training using a random forest classifier and real-time inference. The core technology, powered by Media Pipe Hands, enables real-time capture and processing of hand landmarks for accurate sign language interpretation. This concept differs from classical network technology based on photon or electron transmission. Underlying principles of quantum theory and several aspects of quantum behavior make quantum networking possible. Here are some important quantum principles are incorporated in this project. The project underscores the potential to positively impact the lives of individuals with hearing impairments and contributes to the broader field of accessible communication systems.
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