Hand Sign Detection Using Deep Learning

Abstract

The hand sign detection is an artificial intelligence system that detects and interprets sign language. Computer vision-based machine learning-based gestures. The system captures hand language gestures using computer vision and machine learning techniques. The system captures hand processes the visual data with deep learning models like and moves through cameras. Models such as Convolutional Neural Networks (CNN) and other AI algorithms. The core idea of this project is to close the gap in communication between deaf or mute people, and non-signers, by turning their hand gestures into text or speech in real-time. the system enhances access and inclusion in education, health care, and customer services. The proposed system incorporates gesture recognition, computer vision, and machine learning algorithms to make sure that the sign language is accurately detected and efficiently. This technology supports real -time communication and promotes equal opportunities for hearing -impaired individuals. hms. The main objective of this project is to bridge the communication gap between deaf or mute individuals and non-signers by converting hand gestures into text or speech in real time. The system improves accessibility and inclusivity in areas such as education, healthcare, and customer service. By integrating gesture recognition, computer vision, and machine learning algorithms, the proposed system ensures accurate and efficient sign language detection. This technology supports real -time communication and promotes equal opportunities for hearing -impaired individuals.