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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 11, ISSUE 7, JULY 2022

HAND GESTURE RECONIGITION for PHYSICALLY CHALLENGED

Sahana Ramesh, Mohan Kumar H P

DOI: 10.17148/IJARCCE.2022.11719

Abstract: Hand gestures are an effective form of communication, particularly when we are speaking to others who cannot comprehend our signing. It's also a crucial component of human-computer interaction. To ensure that listeners comprehend what speakers are attempting to say, understanding hand gesture is crucial. Speaking will be helpful for the deaf and the dumb, and the speaking mouth will be helpful for the stupid. Convolutional Neutral Networks (CNN) are frequently used to categorise photographs of hand gestures. Voice recognition is complemented by the conversion of hand movements into text picture manipulation. It offers more accuracy.

Keywords: CNN, Image Processing, Deep Learning, Feature extraction, Vision based system.

How to Cite:

[1] Sahana Ramesh, Mohan Kumar H P, “HAND GESTURE RECONIGITION for PHYSICALLY CHALLENGED,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2022.11719