| Título |
Handwritten Digit Classification Based on Alpha-Beta Associative Model |
| Tipo |
Congreso |
| Sub-tipo |
SCOPUS |
| Descripción |
Lecture Notes in Computer Science; 13th Iberoamerican Congress on Pattern Recognition |
| Resumen |
In this paper we present a new model appropriate for pattern recognition tasks. This new model, called ?? Associative Model, arises when taking theoretical elements from the ?? associative memories, and they are merged with several new mathematical transforms. When applied to handwritten digits recognition, namely in the MNIST database, the ?? Associative Model exhibits competitive results against some of the most widely known algorithms currently available in scientific literature. |
| Observaciones |
Progress in Pattern Recognition, Image Analysis and Applications, CIARP 2008; (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Code 74234 |
| Lugar |
La Habana |
| País |
Cuba |
| No. de páginas |
437-444 |
| Vol. / Cap. |
5197 |
| Inicio |
2008-09-09 |
| Fin |
2008-09-12 |
| ISBN/ISSN |
978-3-540-85919-2 |
