This paper reports the performance of several neural network models on the problem of
multi-font character recognition. The networks are trained on machine generated, upper-
case English letters in selected fonts. The task is to recognize the same letters in different
fonts. The results presented here were produced by back-propagation networks, radial basis
networks and a new hybrid algorithm which is a combination of the two. These results are
compared to those of the Hogg-Hubermann model as well as to those of nearest neighbor …