Handwritten Digit Recognition Based on Contour and Statistic Feature;

Handwritten Digit Recognition of an Integrated BP Neural Network;

A handwritten digit recognition system based on Adaboost algorithm was introduced in this paper.

This paper studies handwritten numeral recognition.

Handwritten numeral recognition belongs to the field of pattern recognition, which is a hot field for a large number of researchers and also is a critical step in entry of information.

A new feature extraction method on handwritten digits recognition system;

A three-stage classification system of handwritten digits recognition is presented for the automatic analysis system in UK psychology test.

In this article, kernel functions are formally discussed in mathematical terms and two of the kernel based learning algorithms: Support Vector Machine (SVM) and Kernel Fisher Discriminant Analysis (KFD) are introduced and applied to handwritten digits recognition.

The handwritten digital recognition was implemented with the advantages of the powerful interface programming capability in VC++.

The handwritten digital recognition is an important problem of pattern recognition field.

To promote the research and application of handwritten digital recognition technology, the superiority of statistical unrelated optimal discriminant transform in handwritten digit recognition was presented and certified.

Fast hand-written digital character recognition based on global feature;