Open Access Open Access  Restricted Access Subscription Access

Handwritten Libretto Recognition Using Multilayer and Cluster Neural Network


Affiliations
1 CSE Department, CIT, Rajanadgaon, India
 

There are different techniques that can be used to recognize handwritten digits and characters. Two techniques discussed in this paper are: Pattern Recognition and Artificial Neural Network. Both techniques are defined and different methods for each technique is also discussed. Bayesian Decision theory, Nearest Neighbor rule, and Linear Classification or Discrimination is types of methods for Pattern Recognition. Shape recognition, Character and Handwritten Digit recognition uses Neural Network to recognize them. Neural Network is used to train and identify written digits. After training and testing, the accuracy rate reached 99%.This accuracy rate is very high.

Keywords

Pattern Recognition, Multilayer, Cluster Neural Network.
User
Notifications
Font Size

Abstract Views: 235

PDF Views: 0




  • Handwritten Libretto Recognition Using Multilayer and Cluster Neural Network

Abstract Views: 235  |  PDF Views: 0

Authors

Anurag Lal
CSE Department, CIT, Rajanadgaon, India

Abstract


There are different techniques that can be used to recognize handwritten digits and characters. Two techniques discussed in this paper are: Pattern Recognition and Artificial Neural Network. Both techniques are defined and different methods for each technique is also discussed. Bayesian Decision theory, Nearest Neighbor rule, and Linear Classification or Discrimination is types of methods for Pattern Recognition. Shape recognition, Character and Handwritten Digit recognition uses Neural Network to recognize them. Neural Network is used to train and identify written digits. After training and testing, the accuracy rate reached 99%.This accuracy rate is very high.

Keywords


Pattern Recognition, Multilayer, Cluster Neural Network.