期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2011
卷号：1
期号：1
页码：1-5
出版社：International Journal of Soft Computing & Engineering
摘要：Handwritten Numeral recognition plays a vital role in postal automation services especially in countries like India where multiple languages and scripts are used .Because of intermixing of these languages; it is very difficult to understand the script in which the pin code is written. Objective of this paper is to resolve this problem through Multilayer feed-forward back-propagation algorithm using two hidden layer. This work has been tested on five different popular Indian scripts namely Devnagri, English, Urdu, Tamil and Telugu. Network was trained to learn its behavior by adjusting the connection strengths on every iteration. The resultant of each presented training pattern was calculated to identify the minima on the error surface for each training pattern. Experiments were performed on samples by using two hidden layers and the results revealed that as the number of hidden layers is increased, more accuracy is achieved in large number of epochs
关键词：Numeral Recognition; Artificial Neural;Network; Supervised learning; Back Propagation Algorithm.
