Optical character recognition: a technology driver for neural networks

It is shown that a neural net can perform handwritten digit recognition with state-of-the-art accuracy. The solution required automatic learning and generalization from thousands of training examples and also required designing into the system considerable knowledge about the task-neither engineering nor learning from examples alone would have sufficed. The resulting network is well suited for implementation on workstations or PCs and can take advantage of digital signal processors (DSPs) or custom VLSI