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@article{157900,
        author = {Vishwas H S and Sourav Nagesh and Suhruth R and Sai Nagesh C H and Manasa Sandeep},
        title = {Sign Language Detection},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {8},
        pages = {215-218},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=157900},
        abstract = {Deaf  people are people at the  deepest psychological level . Many of these people have not been exposed to sign language, and knowing that they can connect with other s by signing 4464s and expressing their love and feelings can bring great relief on a psychological level. It has been observed that approximately 5% of the world's  population suffers from hearing loss. Deaf and mute people use sign language as the primary means of expressing their thoughts and ideas to those around them. Uses a variety of hand and body gestures. People use sign language to It is presented in a way that reduces the communication gap with the general public.This project allows people to communicate with the character 's hand poses to recognize various gesture-based characters . The controller for this assistive software is a  designed to process images of gestures, recognizing characters using  different image processing techniques and  deep  learning models. The characters are converted to  speech in real time using the  text-to-speech engine.},
        keywords = {OpenCV,Python,facial recognition,LSTM,SVM,
CNN,RNN,ANN.},
        month = {},
        }