A hierarchical neural network architecture for handwritten numeral recognition

@article{Cao1997AHN,
  title={A hierarchical neural network architecture for handwritten numeral recognition},
  author={Jun Cao and Majid Ahmadi and Malayappan Shridhar},
  journal={Pattern Recognition},
  year={1997},
  volume={30},
  pages={289-294}
}
This paper presents a hierarchical neural network architecture for recognition of handwritten numeral characters. In this new architecture, two separately trained neural networks connected in series, use the pixels of the numeral image as input and yield ten outputs, the largest of which identifies the class to which the numeral image belongs. The first neural network generates the principal components of the numeral image using Oja's rule, while the second neural network uses an unsupervised… CONTINUE READING
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