Face Recognition with Rough-Neural Network:

Face Detection with methods based on color by using Artificial Neural Network

The face Detection methodsis used in order to provide security. The mentioned methods problems are that it cannot be categorized because of the great differences and varieties in the face of individuals. In this paper, face Detection methods has been presented for overcoming upon these problems based on skin color datum. The researcher gathered a face database of 30 individuals consisting of ov...

Face Recognition with Rough-Neural Network: A Rule Based Approach

Information Granulation and Pattern Recognition

We discuss information granulation applications in pattern recognition. The chapter consists of two parts. In the first part, we present applications of rough set methods for feature selection in pattern recognition. We emphasize the role of different forms of reducts that are the basic constructs of the rough set approach in feature selection. In the overview of methods for feature selection, ...

Identification of Multiple Input-multiple Output Non-linear System Cement Rotary Kiln using Stochastic Gradient-based Rough-neural Network

Because of the existing interactions among the variables of a multiple input-multiple output (MIMO) nonlinear system, its identification is a difficult task, particularly in the presence of uncertainties. Cement rotary kiln (CRK) is a MIMO nonlinear system in the cement factory with a complicated mechanism and uncertain disturbances. The identification of CRK is very important for different pur...

Rough Sets Methods in Feature Reduction and Classification

The paper presents an application of rough sets and statistical methods to feature reduction and pattern recognition. The presented description of rough sets theory emphasizes the role of rough sets reducts in feature selection and data reduction in pattern recognition. The overview of methods of feature selection emphasizes feature selection criteria, including rough set-based methods. The pap...