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.
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Mejías, A., Sánchez, O., Romero, S. (2007). Automatic Selection of Input Variables and Initialization Parameters in an Adaptive Neuro Fuzzy Inference System. Application for Modeling Visual Textures in Digital Images. In: Sandoval, F., Prieto, A., Cabestany, J., Graña, M. (eds) Computational and Ambient Intelligence. IWANN 2007. Lecture Notes in Computer Science, vol 4507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73007-1_50
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DOI: https://doi.org/10.1007/978-3-540-73007-1_50
Publisher Name: Springer, Berlin, Heidelberg
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