INTELLIGENT COMPUTING FOR THE CLASSIFICATION OF WHEAT SEEDS

Abstract

Kohonen's self-organized maps (SOM) are a type of artificial neural networks of unsupervised learning that allows the identification of patterns between data by measuring the distances between them to form clusters by meeting one representative for each group. In this article we present the SOM algorithm to represent data maps, we will use a program in Matlab with the tool SOM toolbox to carry out the classification of three types of wheat seeds, based on the attributes of the same.

Keywords: SOM, training, artificial neural network, database, classification.

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