Handwritten digit recognition network
27 November 1989
Handwritten digit recognition network from AT&T, vision model published 1989-11-27. Notable for: historical significance.
Abstract
We present an application of back-propagation networks to handwritten digit recognition. Minimal preprocessing of the data was required, but architecture of the network was highly constrained and specifically designed for the task. The input of the network consists of normalized images of isolated digits. The method has 1% error rate and about a 9% reject rate on zipcode digits provided by the U.S. Postal Service.
Sources: Epoch AI. This entry was generated from a dataset and has not been edited by hand.