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本文的题目是基于分形和遗传算法的人脸识别方法,对有限人群提出一种采用分形特征和遗传聚类的识别方法: 将图像分成很多小区域, 分别计算各个区域的分形特征, 以充分利用图像二维信息 同一个模式有多个样本, 通过遗传算法进行聚类以得到最优解实现不变性识别. 最后采用ORL 人脸图像库的一组图像对比了新方法、本征脸法和自联想神经网络方法, 结果表明该方法的识别率, 与本征脸法相似, 比自联想神经网络高.-The title of this article is based on fractal and genetic algorithms for face recognition method, a crowd of limited use of fractal characteristics and the identification of genetic clustering methods: the image is divided into many small regions, each region were calculated fractal characteristics, to take full advantage of two-dimensional image information with a model for a number of samples, through the genetic clustering algorithm in order to obtain the optimal solution to achieve invariant recognition. Finally, using ORL face image database of a group of image contrast of the new methods, eigenface law and auto-associative neural network methods, results show that the method of recognition rate, with the eigenface method is similar to auto-associative neural network than high.
Date : 2026-01-03 Size : 372kb User : 阳关

在本讲义中,我们将着重讲述一些数学建模中常用的算法,包括神经网络算法、遗传算 法、模拟退火算法和模糊数学方法。用这些算法可以较容易地解决一些很复杂的,常规算法很难解决的问题。-In this lecture, we will focus on about a number of commonly used mathematical modeling algorithms, including neural network algorithm, genetic algorithm Method, simulated annealing algorithm and fuzzy mathematics. These algorithms can be more easily used to solve some very complex and difficult to solve the problem of conventional algorithms.
Date : 2026-01-03 Size : 267kb User : drawsalt
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