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….

1. “RECOGNITION OF CHARACTERS &DIGITS”
“Recognition of Assamese Vowels Consonants and
Digits”
Presented By:
Sri Uday Saikia(Roll no. xxxxxx

2. 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.


3. 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.

4. GCR MODEL

6. BACK GROUND INFORMATION

7. PREPROCESSING

8. ARCHITECTURE OF RACD
CHARACTERS AND DIGITS)
(RECOGNITION OF ASSAMESE

9. ANN(ARTIFICIAL NEURAL NETWORK)

1. Biological Neuron

10. HOW THE HUMAN BRAIN LEARNS?

Components of a neuron

11. 
Synapse

12. 
The Neuron Model

13. A typical Feed-forward neural network model

14. THE NEURAL NETWORK

15. Training of characters using neural networks

16. 
Regression of trained neural networks

17. Training state of neural networks

18. GRAPHICAL USER INTERFACE….