Non-Correlated Character Recognition using Artificial Neural Network

06/19/2013
by   Tirtharaj Dash, et al.
0

This paper investigates a method of Handwritten English Character Recognition using Artificial Neural Network (ANN). This work has been done in offline Environment for non correlated characters, which do not possess any linear relationships among them. We test that whether the particular tested character belongs to a cluster or not. The implementation is carried out in Matlab environment and successfully tested. Fifty-two sets of English alphabets are used to train the ANN and test the network. The algorithms are tested with 26 capital letters and 26 small letters. The testing result showed that the proposed ANN based algorithm showed a maximum recognition rate of 85

READ FULL TEXT
research
06/19/2013

English Character Recognition using Artificial Neural Network

This work focuses on development of a Offline Hand Written English Chara...
research
08/30/2009

Handwritten Farsi Character Recognition using Artificial Neural Network

Neural Networks are being used for character recognition from last many ...
research
01/20/2013

English Sentence Recognition using Artificial Neural Network through Mouse-based Gestures

Handwriting is one of the most important means of daily communication. A...
research
12/23/2013

Automated Coin Recognition System using ANN

Coins are integral part of our day to day life. We use coins everywhere ...
research
02/02/2023

Simple method for detecting sleep episodes in rats ECoG using machine learning

In this paper we propose a new method for the automatic recognition of t...
research
12/17/2018

Persian Vowel recognition with MFCC and ANN on PCVC speech dataset

In this paper a new method for recognition of consonant-vowel phonemes c...
research
07/09/2015

Neural Network Classifiers for Natural Food Products

Two cheap, off-the-shelf machine vision systems (MVS), each using an art...

Please sign up or login with your details

Forgot password? Click here to reset