Research · 1989
A convolutional network on zip codes
A Bell Labs group trained a convolutional network to read handwritten postal codes and ran it on real United States mail.
Why it matters
The first back-propagation-trained network doing paid work, and the first convolutional architecture with learned features.
The constraints of the task were built into the architecture itself: local receptive fields, shared weights, subsampling. That cut the parameter count by an order of magnitude and let the network train on the data available. Training took three days on a SUN workstation; the same run takes minutes today.
What the record does not claim. An earlier version said the system read about 10 percent of US cheques in the early 1990s; no source of the record says so, and the developers' own CVPR-97 paper dates the cheque reader's first deployment in a bank to June 1996, which is a record of its own.
Event record
- Event date
- 1989
- Timeline date
- Event date
- Verification
- Sources gathered automatically · September 17, 2026
- Lines
- ID
- evt-0159
Neural Computation volume 1, issue 4, 1989.
Records that link to this one
- Extends LeNet-5 and MNIST
The full account of the architecture shown on zip codes in 1989.
Gradient-Based Learning Applied to Document Recognition - Related Falcon: a neural network against card fraud
The second neural network to do paid work at national scale: there, mail and cheques; here, card payment authorisation.
- Related NIST's shared test on handwritten characters
Among the participants were four AT&T systems, from the laboratory that trained the convolutional network on zip codes.
- Builds on A convolutional network reads cheques in banks
The character recognizer is a convolutional network; the paper cites the 1989-1990 work on zip codes as its origin.
Global training of document processing systems using graph transformer networks (L. Bottou, Y. Bengio, Y. Le Cun), CVPR-97, San Juan, 17-19 June 1997, pp. 489-494 - Related ANNA: a convolutional network on an analog chip
The chip runs a handwritten digit recognizer from the same Bell Labs group, a convolutional network previously trained and run on ordinary computers.