Handwritten Digit Recognition: A Neural Network Demo

Berend-Jan van der Zwaag

doi:10.1007/3-540-45493-4_75

Handwritten Digit Recognition: A Neural Network Demo

Berend-Jan van der Zwaag

Universiteit Twente

Onderzoeksoutput: Contribution to conference proceeding › Academic › peer review

Samenvatting

A handwritten digit recognition system was used in a demonstration project to visualize artificial neural networks, in particular Kohonen's self-organizing feature map. The purpose of this project was to introduce neural networks through a relatively easy-to-understand application to the general public. This paper describes several techniques used for preprocessing the handwritten digits, as well as a number of ways in which neural networks were used for the recognition task. Whereas the main goal was a purely educational one, a moderate recognition rate of 98% was reached on a test set. © Springer-Verlag 2001.

Originele taal-2	English
Titel	International Conference on Computational Intelligence
Subtitel	Fuzzy Days
Uitgeverij	Springer Nature
Pagina's	762-771
Aantal pagina's	10
ISBN van elektronische versie	978-3-540-45493-9
ISBN van geprinte versie	978-3-540-42732-2
DOI's	https://doi.org/10.1007/3-540-45493-4_75
Status	Published - 1 jan. 2001
Extern gepubliceerd	Ja
Evenement	Computational Intelligence. Theory and Applications: 7th Fuzzy Days Dortmund - Dortmund, Germany Duur: 1 okt. 2001 → 3 okt. 2001

Conference

Conference	Computational Intelligence. Theory and Applications
Land/Regio	Germany
Stad	Dortmund
Periode	1/10/01 → 3/10/01

Keywords

neurale netwerken
computationele intelligentie

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10.1007/3-540-45493-4_75

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title = "Handwritten Digit Recognition: A Neural Network Demo",

abstract = "A handwritten digit recognition system was used in a demonstration project to visualize artificial neural networks, in particular Kohonen's self-organizing feature map. The purpose of this project was to introduce neural networks through a relatively easy-to-understand application to the general public. This paper describes several techniques used for preprocessing the handwritten digits, as well as a number of ways in which neural networks were used for the recognition task. Whereas the main goal was a purely educational one, a moderate recognition rate of 98\% was reached on a test set. {\textcopyright} Springer-Verlag 2001.",

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doi = "10.1007/3-540-45493-4\_75",

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PY - 2001/1/1

Y1 - 2001/1/1

N2 - A handwritten digit recognition system was used in a demonstration project to visualize artificial neural networks, in particular Kohonen's self-organizing feature map. The purpose of this project was to introduce neural networks through a relatively easy-to-understand application to the general public. This paper describes several techniques used for preprocessing the handwritten digits, as well as a number of ways in which neural networks were used for the recognition task. Whereas the main goal was a purely educational one, a moderate recognition rate of 98% was reached on a test set. © Springer-Verlag 2001.

AB - A handwritten digit recognition system was used in a demonstration project to visualize artificial neural networks, in particular Kohonen's self-organizing feature map. The purpose of this project was to introduce neural networks through a relatively easy-to-understand application to the general public. This paper describes several techniques used for preprocessing the handwritten digits, as well as a number of ways in which neural networks were used for the recognition task. Whereas the main goal was a purely educational one, a moderate recognition rate of 98% was reached on a test set. © Springer-Verlag 2001.

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ER -

Handwritten Digit Recognition: A Neural Network Demo

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