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http://hdl.handle.net/2080/3414
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DC Field | Value | Language |
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dc.contributor.author | Gupta, Devashish | - |
dc.contributor.author | Mohanty, Jaganath Prasad | - |
dc.contributor.author | Swain, Ayas Kant | - |
dc.contributor.author | Mahapatra, Kamalakanta | - |
dc.date.accessioned | 2019-12-27T05:48:53Z | - |
dc.date.available | 2019-12-27T05:48:53Z | - |
dc.date.issued | 2019-12 | - |
dc.identifier.citation | 5th IEEE International Symposium on Smart Electronic Systems ( IEEE-iSES 2019 ) Rourkela, India, 16- 18 December 2019. | en_US |
dc.identifier.uri | http://hdl.handle.net/2080/3414 | - |
dc.description | Copyright of this document belongs to proceedings publisher. | en_US |
dc.description.abstract | Hand 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.subject | Deep learning | en_US |
dc.subject | Hand gesture recognition | en_US |
dc.subject | Sign language interpreter | en_US |
dc.subject | ASL | en_US |
dc.subject | Human-machine interface | en_US |
dc.subject | Convolutional neural network | en_US |
dc.subject | Raspberry pi | en_US |
dc.title | AutoGstr: Relatively Accurate Sign Language Interpreter | en_US |
dc.type | Article | en_US |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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2019_ISES_JPMohanty_AutoGstr.pdf | Conference paper | 563.71 kB | Adobe PDF | View/Open |
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