Automatic Selection of Input Variables and Initialization Parameters in an Adaptive Neuro Fuzzy Inference System. Application for Modeling Visual Textures in Digital …

A Mejías, O Sánchez, S Romero - International Work-Conference on …, 2007 - Springer
A Mejías, O Sánchez, S Romero
International Work-Conference on Artificial Neural Networks, 2007Springer
In this paper we present a method for the automatic selection of input variables and some
previous parameters, such as number and type of membership functions, in an Adaptive
Neuro Fuzzy Inference System (ANFIS) using a Genetic Algorithm with a new fitness
function. Both of them constitute a design scheme that we will use for modeling the
perception of textures in Digital I-mages. Some examples are presented, training ANFIS with
this scheme for mo-deling the following visual textures: coarseness, directionality and …
Abstract
In this paper we present a method for the automatic selection of input variables and some previous parameters, such as number and type of membership functions, in an Adaptive Neuro Fuzzy Inference System (ANFIS) using a Genetic Algorithm with a new fitness function. Both of them constitute a design scheme that we will use for modeling the perception of textures in Digital I-mages. Some examples are presented, training ANFIS with this scheme for mo-deling the following visual textures: coarseness, directionality and regularity.
Springer
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