基于遗传方法的属性向量优化:在字符分类中的应用

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI:10.1109/CGIV.2016.85

Benchaou Soukaina, M. Nasri, Fouad Aouinti, Khalid Zinedine, Ouafae El Melhaoui

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引用次数: 0

摘要

为分类选择参数是一个精细的过程。本文提出了一种用遗传算法选择参数的方法，该方法通过最小化代价函数来优化参数的选择。这个函数是由Trace条件定义的。在一些字符图像上验证了该方法的有效性。该算法收敛速度快，逼近最优解。

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Optimization of the Attribute Vector by Genetic Approach: Application to the Classification of Characters

Selecting the parameters for the classification is a delicate process. We present in this paper a method for selecting the parameters by the genetic algorithm which optimizes the choice of parameters by minimizing a cost function. This function is defined by a Trace criterion. The approach is validated on some characters images. The proposed algorithm gives a fast convergence towards the optimal solution.

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2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)

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