Performance optimization and comparative analysis of neural networks for handwritten Devanagari character recognition

Devanagari script has character set with rich structural features that makes the recognition of unconstrained handwritten Devanagari characters difficult However, these features can be used to divide the characters into different categories. This paper presents few techniques for optimizing the recognition accuracy at pre-classification stage, feature extraction stage and recognition stage. Initially, the pre-classification of the characters is done into different classes using various structural features. Then features are extracted using optimized feature extraction techniques. Finally, the recognition is done using neural network. In this paper, different neural networks are implemented and their performances are analyzed.

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