Two-tier architecture for unconstrained handwritten character recognition

@inproceedings{Reddy2002TwotierAF,
  title={Two-tier architecture for unconstrained handwritten character recognition},
  author={N. V. Subba Reddy},
  year={2002}
}
In this paper, we propose an approach that combines the unsupervised and supervised learning techniques for unconstrained handwritten numeral recognition. This approach uses the Kohonen self-organizing neural network for data classification in the first stage and the learning vector quantization (LVQ) model in the second stage to improve classification accuracy. The combined architecture performs better than the Kohonen self-organizing map alone. In the proposed approach, the collection of… CONTINUE READING
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