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1. Overview 2.Development of System 3.GCR Model 4.Proposed model 5.Back ground Information 6. Preprocessing 7.Architecture 8.ANN(Artificial Neural Network) 9.How the Human Brain Learns? 10.Synapse 11.The Neuron Model 12.A typical Feed-forward neural network model 13.The neural Network 14.Training of characters using neural networks 15.Regression of trained neural networks 16.Training state of neural networks 17.Graphical user interface….
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“RECOGNITION OF CHARACTERS &DIGITS”
“Recognition of Assamese Vowels Consonants and Digits”
Presented By:
Sri Uday Saikia(Roll no. xxxxxx
PROJECT OVERVIEW: one of the challenging computational processes. There is competition between the speed and
efficiency. The human mind can easily decipher these
handwritten characters easily, accurately and speedily.
The human mind can do it because of the presence of densely neural network in his mind.
DEVELOPMENT OF RACD SYSTEM
The problem defines in the acquisition process of an RACD system can be justified by training of neural networks in reconstruction of Assamese characters & Digits. First of all, the system by offline handwritten different shapes of Assamese characters is taught. On the basis of this image model database, character sets are matched and classify the reconstructed image.
GCR MODEL
BACK GROUND INFORMATION
PREPROCESSING
ARCHITECTURE OF RACD (RECOGNITION OF ASSAMESE CHARACTERS AND DIGITS)
ANN(ARTIFICIAL NEURAL NETWORK)
1. Biological Neuron
HOW THE HUMAN BRAIN LEARNS?
Components of a neuron
Synapse
The Neuron Model
A typical Feed-forward neural network model
THE NEURAL NETWORK
Training of characters using neural networks
Regression of trained neural networks
Training state of neural networks
GRAPHICAL USER INTERFACE….
