A Comparative Study of Neural Network Algorithms Applied to Optical Character Recognition

@inproceedings{Smagt1990ACS,
  title={A Comparative Study of Neural Network Algorithms Applied to Optical Character Recognition},
  author={Patrick van der Smagt},
  booktitle={IEA/AIE},
  year={1990}
}
Three simple general purpose networks are tested for pattern classification on an optical character recognition problem. The feed-forward (multi-layer perceptron) network, the Hopfield network and a competitive learning network are compared. The input patterns are obtained by optically scanning images of printed digits and uppercase letters. The resulting data is used as input for the networks with two-state input nodes; for others, features are extracted by template matching and pixel counting… CONTINUE READING

Citations

Publications citing this paper.
Showing 1-10 of 11 extracted citations

A Framework for Using Neural Networks for Web Proxy Cache Replacement

Hala ElAarag, Jake Cobb Stetson
2006
View 14 Excerpts
Highly Influenced

Enhancing Thinning Method for Malaysian Car Plates Recognition

Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007) • 2007

One Shot Associative Memory Method for Distorted Pattern Recognition

Australian Conference on Artificial Intelligence • 2007
View 1 Excerpt

Similar Papers

Loading similar papers…