Identifying images of handwritten digits using deep learning in H2O

Automatic digit recognition is of popular interest today. Deep learning techniques make it possible for object recognition in image data. Perceiving the digit has turned into a fundamental part as far as certifiable applications. Since, digits are composed in various styles in this way to distinguis...

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Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2017-11, Vol.263 (4)
Main Authors: Sadhasivam, Jayakumar, Charanya, R, Harish Kumar, S, Srinivasan, A
Format: Article
Language:English
Subjects:
Artificial neural networks
Counterfeit
Deep learning
Digits
Handwriting recognition
Machine learning
Object recognition
Pictures
Vector quantization
Online Access:Get full text
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Summary:Automatic digit recognition is of popular interest today. Deep learning techniques make it possible for object recognition in image data. Perceiving the digit has turned into a fundamental part as far as certifiable applications. Since, digits are composed in various styles in this way to distinguish the digit it is important to perceive and arrange it with the assistance of machine learning methods. This exploration depends on supervised learning vector quantization neural system arranged under counterfeit artificial neural network. The pictures of digits are perceived, prepared and tried. After the system is made digits are prepared utilizing preparing dataset vectors and testing is connected to the pictures of digits which are separated to each other by fragmenting the picture and resizing the digit picture as needs be for better precision.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/263/4/042033