Sign Language Detection with CNN
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Published:2022-05-31
Issue:5
Volume:10
Page:471-484
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ISSN:2321-9653
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Container-title:International Journal for Research in Applied Science and Engineering Technology
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language:
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Short-container-title:IJRASET
Author:
Bhamare Suyog,Shinde Abhishek,Palve Rahul,Gharu A. N.
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.
Publisher
International Journal for Research in Applied Science and Engineering Technology (IJRASET)
Subject
General Earth and Planetary Sciences,General Environmental Science
Cited by
1 articles.
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