Experiments with various neural architectures for handwritten character recognition

In this research we address the problem of recognition of isolated handwritten characters. Handwritten character recognition has been a topic of research for a long period of time. It has been argued that this problem is difficult to model using classical modeling techniques, and that neural networks offer a new perspective to approaching this problem. This paper outlines the experimental evidence we have compiled while investigating possible approaches to handwritten character recognition. It is the hypothesis of our approach that handwritten character recognition is a pattern recognition problem and that there exists a set of unique features in the data which can be used for classification