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dc.contributor.authorGupta, Devashish-
dc.contributor.authorMohanty, Jaganath Prasad-
dc.contributor.authorSwain, Ayas Kant-
dc.contributor.authorMahapatra, Kamalakanta-
dc.identifier.citation5th IEEE International Symposium on Smart Electronic Systems ( IEEE-iSES 2019 ) Rourkela, India, 16- 18 December 2019.en_US
dc.descriptionCopyright of this document belongs to proceedings publisher.en_US
dc.description.abstractHand gesture recognition is the one of the method to identify the hand position, its pattern and then translate it to the corresponding meaning or purpose. This paper contributes a real time sign language interpretation of hand gestures based on deep convolutional neural networks with focus on development of a cost-effective and efficient hardware prototype for communication ease with deaf and dumb people.en_US
dc.subjectDeep learningen_US
dc.subjectHand gesture recognitionen_US
dc.subjectSign language interpreteren_US
dc.subjectHuman-machine interfaceen_US
dc.subjectConvolutional neural networken_US
dc.subjectRaspberry pien_US
dc.titleAutoGstr: Relatively Accurate Sign Language Interpreteren_US
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