Symmetric Axis Based Off-Line Odia Handwritten Character and Numeral Recognition

Author(s):  
Abhisek Sethy ◽  
Prashanta Kumar Patra ◽  
SoumyaRanjan Nayak ◽  
Pyari Mohan Jena
2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Pratibha Singh ◽  
Ajay Verma ◽  
Narendra S. Chaudhari

The paper is about the application of mini minibatch stochastic gradient descent (SGD) based learning applied to Multilayer Perceptron in the domain of isolated Devanagari handwritten character/numeral recognition. This technique reduces the variance in the estimate of the gradient and often makes better use of the hierarchical memory organization in modern computers.L2-weight decay is added on minibatch SGD to avoid overfitting. The experiments are conducted firstly on the direct pixel intensity values as features. After that, the experiments are performed on the proposed flexible zone based gradient feature extraction algorithm. The results are promising on most of the standard dataset of Devanagari characters/numerals.


Informatica ◽  
2018 ◽  
Vol 29 (3) ◽  
pp. 399-420
Author(s):  
Alessia Amelio ◽  
Darko Brodić ◽  
Radmila Janković

2016 ◽  
Vol 2 (4) ◽  
pp. 26
Author(s):  
VOHRA UJWAL SINGH ◽  
DWIVEDI SHRI PRAKASH ◽  
MANDORIA H.L ◽  
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