DocumentCode :
3761010
Title :
Associative Memory Model for Distorted On-Line Devanagari Character Recognition
Author :
Gaurav Pagare;Karun Verma
Author_Institution :
Comput. Sci. &
fYear :
2015
Firstpage :
46
Lastpage :
49
Abstract :
Machine and human interaction is very essential in today´s scenario. This interaction would make search engines, social media, artificial intelligence, cognitive computing more interactive and user friendly. Handwriting recognition is the systematic process of identifying the characters, numbers and symbols present in the handwritten document. In the current work, a recognition model for digitizing handwritten Devanagari characters proposed. Auto associative recognition technique for Devanagari characters and numerals proposed in the current work by using classifiers. To solve recognition problem a dynamic model based on Hopfield neural network deployed. The model performs operation in parallel making it faster and optimal in solving recognition problem.
Keywords :
"Character recognition","Handwriting recognition","Neurons","Image recognition","Hidden Markov models","Associative memory","Hopfield neural networks"
Publisher :
ieee
Conference_Titel :
Advances in Computing and Communications (ICACC), 2015 Fifth International Conference on
Print_ISBN :
978-1-4673-6993-0
Type :
conf
DOI :
10.1109/ICACC.2015.42
Filename :
7433773
Link To Document :
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