Handwritten Digit Classification Based on Alpha-Beta Associative Model

Authors:
Luis Octavio López-Leyva;Cornelio Yáñez-Márquez;Rolando Flores-Carapia;Oscar Camacho-Nieto
Affiliations:
IPN Centro de Investigación en Computación Juan de Dios Bátiz s/n esq. Miguel Othón de Mendizábal Unidad Profesional Adolfo López Mateos Del. Gustavo A. Madero, M ...;IPN Centro de Investigación en Computación Juan de Dios Bátiz s/n esq. Miguel Othón de Mendizábal Unidad Profesional Adolfo López Mateos Del. Gustavo A. Madero, M ...;IPN Centro de Investigación en Computación Juan de Dios Bátiz s/n esq. Miguel Othón de Mendizábal Unidad Profesional Adolfo López Mateos Del. Gustavo A. Madero, M ...;IPN Centro de Investigación en Computación Juan de Dios Bátiz s/n esq. Miguel Othón de Mendizábal Unidad Profesional Adolfo López Mateos Del. Gustavo A. Madero, M ...
Venue:
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Year:
2008

Citing 4
Cited 0

Training Invariant Support Vector Machines

Machine Learning
Best Practices for Convolutional Neural Networks Applied to Visual Document Analysis

ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Analysis of errors of handwritten digits made by a multitude of classifiers

Pattern Recognition Letters - Special issue: In memoriam Azriel Rosenfeld
Handwritten digit classification using higher order singular value decomposition

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we present a new model appropriate for pattern recognition tasks. This new model, called 茂戮驴βAssociative Model, arises when taking theoretical elements from the 茂戮驴βassociative memories, and they are merged with several new mathematical transforms. When applied to handwritten digits recognition, namely in the MNIST database, the 茂戮驴βAssociative Model exhibits competitive results against some of the most widely known algorithms currently available in scientific literature.