Recent works on character recognition involves in different applications like security,
biometrics etc. In most of the works Convolutional neural networks (CNN) are used for image …

In recent years, the non-handcrafted feature extraction methods have gained increasing
popularity for solving pattern classification tasks due to their inherent ability to extract robust …

Character recognition is a challenging area in Machine Learning, Pattern Recognition or
Image Processing. The accuracy to recognize handwritten character by human is far better …

Feature representation in the form of spatio-spectral decomposition is one of the robust
techniques adopted in automatic handwritten character recognition systems. In this regard …

Character recognition in handwritten data is a challenging work as the writing style varies
from person to person. Choosing a method for handwritten numeral recognition is also …

Optical character recognition is a kind of report picture investigation where filtered images
that contain either machine printed or composed by hand content commitment to an optical …

The literature on Odia optical character recognition (OCR) has shown notable gains made in
designing models using only 47–51 classes of Odia allographs. However, these models do …

Automatic character recognition is one of the challenging fields in pattern recognition
especially for handwritten Odia characters as many of these characters are similar and …