Handwritten Digit Recognition with a Back-Propagation Network

neural information processing systemsPublished 1 January 1989

Yann LeCun, Bernhard E. Boser, John S. Denker, D. Henderson, Richard Howard, Wayne E. Hubbard

Citations3,637

TL;DR

Minimal preprocessing of the data was required, but architecture of the network was highly constrained and specifically designed for the task, and has 1% error rate and about a 9% reject rate on zipcode digits provided by the U.S. Postal Service.

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.

Keywords

Computer Science

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