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@article{158225,
        author = {Nadeem Gulam and Neha Pandey and Medha R and Rakshith Vk and Vasudeva G},
        title = {Survey on Sign Language Identification Using Deep Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {9},
        pages = {170-173},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=158225},
        abstract = {Hearing and speech impairment is one of the most challenging problems faced by people with disabilities. The proposed system provides a platform which helps people with speech disability communicate with the world. Sign language is the mode of communication for speech deprived people and other people cannot interpret their language effectively and this causes a hindrance to them. And as a consequence, people with disabilities who are a minority in the community cannot perform even basic tasks. So, the idea proposed is a system which converts Sign Language (SL) to text and speech output. This is implemented using convolutional neural networks (CNN) to extract efficient hand features to identify the hand gestures according to Sign Language. Hence, this model helps in recognizing the hand gestures of people with disabilities and converting them to text and speech to allow them to communicate effectively.},
        keywords = {ConvolutionalNeural Networks. },
        month = {},
        }