This paper describes the construction of a system that recognizes handprinted digits, using a combination of classical techniques and neural-net methods. The system has been trained and tested on real-world data, derived from zip codes seen on actual U.S. Mail. The system rejects a small percentage of the examples as unclassifiable, and achieves a very low error rate on the remaining examples. The system compares favorably with other state-of-the art recognizers. While some of the methods are specific to this task, it is hoped that many of the techniques will be applicable to a wide range of recognition tasks.
['John S. Denker', 'William Gardner', 'Hans Peter Graf', 'Donnie Henderson', 'R. E. Howard', 'Wayne E. Hubbard', 'L. D. Jackel', 'Henry S. Baird', 'Isabelle Guyon']
Neural Network Recognizer for Hand-Written Zip Code Digits