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@article{167934,
        author = {K. Vanitha Sri and Ahmed Aabidh Hajji and Ashhar Nawaz Khan and Mohamed Maaz and Muaz Ameen Sheriff Ajass},
        title = {MULTI HAND SIGN LANGUAGE DETECTION AND TRANSLATION IN REAL TIME USING MEDIAPIPE},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {4},
        pages = {1708-1713},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=167934},
        abstract = {This project offers a solution to bridge the communication gap between sign language users and non-users using the Mediapipe library. By utilizing computer vision techniques, the system detects and interprets multiple sign language gestures in real time. Mediapipe's pre-trained deep learning models handle tasks like hand tracking and gesture recognition, ensuring accurate sign language detection without needing custom algorithms. With real-time processing, the system facilitates smooth interaction, making communication more inclusive. It can recognize multiple gestures at once, enabling users to express themselves naturally. This project enhances accessibility and fosters inclusivity for individuals with hearing impairments by using advanced sign language detection tools},
        keywords = {},
        month = {September},
        }