Granular neural networks (GNN) are designed to process complex non-numerical data or
the combination of numerical and non-numerical data. The concept of “granules” here refers …

An enhanced fuzzy min-max (EFMM) network is proposed for pattern classification in this
paper. The aim is to overcome a number of limitations of the original fuzzy min-max (FMM) …

Hyperbox classifier is an efficient tool for modern pattern classification problems due to its
transparency and rigorous use of Euclidian geometry. Fuzzy min-max (FMM) network …

Differential evolution (DE) algorithm suffers from high computational time due to slow nature
of evaluation. Micro-DE (MDE) algorithms utilize a very small population size, which can …

In this article, we propose a design and evaluation framework of granular neural networks
realized in the presence of information granules. Neural networks realized in this manner …

Multiobjective interval linear programming (MOILP) is one of the most important approaches
to real-world optimization problems involving multiple conflicting objectives under …

A biometric system provides automatic identification of an individual based on a unique
feature or characteristic possessed by the individual. Unlike other biometric such as …

This paper presents a new algorithm capable of improving the accuracy level of a laser
pointer detector used within an interactive control device system. A genetic programming …

Active appearance model (AAM) is one of the most popular model‐based approaches that
have been extensively used to extract features by highly accurate modeling of human faces …

In this chapter a new method for response integration, based on Choquet Integral is
presented. A type-1 fuzzy system for edge detections based in Sobel and Morphological …