Comparing Performance of Neural Networks Recognizing Machine Generated Characters
نویسندگان
چکیده
Neural networks are a popular tool in the area of pattern recognition. However, since a very large number of neural network architectures exist, it has not been established which one is the most efficient. In this paper we compare the performance of three neural network architectures: Kohonen’s self-organizing network, probabilistic neural network, and a modified backpropagation applied to a simplified character recognition problem.
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