Abstract
Abstract: Sign language is one of the oldest and most natural forms of language for com- munication, but since most people do not know sign language and interpreters are very difficult to come by, we have come up with a real time method using neural networks for fingerspelling based American sign language. In our method, the hand is first passed through a filter and after the filter is applied the hand is passed through a classifier which predicts the class of the hand gestures. Our method provides 95.7% accuracy for the 26 letters of the alphabet.
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