A classifier for Bangla handwritten numeral recognition

Authors:
Ying Wen;Lianghua He
Affiliations:
Department of Computer Science and Technology, East China Normal University, Shanghai 200062, China and Pediatric Brain Imaging Laboratory, Columbia University, New York, NY 10032, USA;Pediatric Brain Imaging Laboratory, Columbia University, New York, NY 10032, USA and Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai 200 ...
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

Citing 16
Cited 1

Introduction to statistical pattern recognition (2nd ed.)

Introduction to statistical pattern recognition (2nd ed.)
The nature of statistical learning theory

The nature of statistical learning theory
Multilayer cluster neural network for totally unconstrained handwritten numeral recognition

Neural Networks
Support Vector Machines for 3D Object Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear component analysis as a kernel eigenvalue problem

Neural Computation
An introduction to support Vector Machines: and other kernel-based learning methods

An introduction to support Vector Machines: and other kernel-based learning methods
A Bootstrap Technique for Nearest Neighbor Classifier Design

IEEE Transactions on Pattern Analysis and Machine Intelligence
Training Support Vector Machines: an Application to Face Detection

CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Fast SVM Training Algorithm with Decomposition on Very Large Data Sets

IEEE Transactions on Pattern Analysis and Machine Intelligence
2005 Special Issue: Constructing Bayesian formulations of sparse kernel learning methods

Neural Networks - 2005 Special issue: IJCNN 2005
Handwritten Bangla numeral recognition system and its application to postal automation

Pattern Recognition
Estimation of Classification Error

IEEE Transactions on Computers
Bayes Classification of Online Arabic Characters by Gibbs Modeling of Class Conditional Densities

IEEE Transactions on Pattern Analysis and Machine Intelligence
Reducing SVM classification time using multiple mirror classifiers

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Neural-network classifiers for recognizing totally unconstrained handwritten numerals

IEEE Transactions on Neural Networks
Face recognition with radial basis function (RBF) neural networks

IEEE Transactions on Neural Networks

Short communication: An improved discriminative common vectors and support vector machine based face recognition approach

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	12.05

Visualization

Abstract

This paper presents a novel pattern classification approach - a kernel and Bayesian discriminant based classifier which utilizes the distribution characteristics of the samples in each class. A kernel combined with Bayesian discriminant in the subspace spanned by the eigenvectors which are associated with the smaller eigenvalues in each class is adopted as the classification criterion. To solve the problem of the matrix inverse, the smaller eigenvalues are substituted by a small threshold which is decided by minimizing the training error in a given database. Application of the proposed classifier to the issue of handwritten numeral recognition demonstrates that it is promising in practical applications.