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@article{160233,
        author = {Amruta Amol Bhawarthi and Yash Kate and Tarun Kasliwal and Manas Kasodekar and Soham Kasurde and Siddhant Kaswa and Vedant Kate},
        title = {Indian Sign Language Recognition System},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {1},
        pages = {227-229},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=160233},
        abstract = {The Indian Sign Language (ISL) Recognition System is a system designed to recognize and interpret ISL gestures made for individuals with hearing and speaking impairments. This system aims to improve communication between the deaf and mute communities. The system utilizes computer vision and machine learning techniques to analyze and categorize the ISL gestures into corresponding words. The system has been trained on a large dataset of ISL gestures to improve its accuracy. The recognition process involves capturing the ISL gestures via a camera, pre-processing the captured data, and passing it through a machine learning model to make a prediction. The system can be used in various applications such as sign language translation, sign language learning, and accessibility technology for the deaf. },
        keywords = {Python, object detection, Indian Sign Language, Image labelling, TensorFlow},
        month = {},
        }