Modular Neural Networks and Type-2 Fuzzy Logic for Face Recognition

O. Mendoza, Guillermo Licea, P. Melin
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引用次数: 30

Abstract

In this paper we present a method for face recognition combining modular neural networks and two interval type-2 fuzzy inference systems (FIS 2) for face recognition. The first FIS 2 is used for edges detection in the training data, and the second one to find the ideal parameters for the Sugeno integral as a decision operator. Fuzzy logic is shown to be a tool that can help improve the results of a neural system facilitating the representation of the human perception.
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模块化神经网络与2型模糊逻辑在人脸识别中的应用
本文提出了一种将模块化神经网络与两个区间2型模糊推理系统(FIS 2)相结合的人脸识别方法。第一个FIS 2用于训练数据的边缘检测,第二个FIS 2用于寻找Sugeno积分的理想参数作为决策算子。模糊逻辑被证明是一种工具,可以帮助改善神经系统的结果,促进人类感知的表征。
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