SIGN LANGUAGE PREDICTION USING CNN









Abstract

Sign language is a form of non-verbal communication in which physical gestures are used to convey important messages, either in the speech area or in conjunction with the spoken word. Sign language includes movements of the hands, face, or other parts of the body. Non-verbal communication such as explicit gestures, proxemics, or collective attention spans differs from touch, which conveys specific messages. This project is for training a Deep Learning algorithm that is able to distinguish images of different sign languages, such as alphabet, and numbers. It is predicted that the success of the results obtained will increase if the CNN method is supported by adding additional output methods and successfully separating the fruit types in the image.


Modules


Algorithms


Software And Hardware