Title :
Type-2 Fuzzy Systems for Improving Training Data and Decision Making in Modular Neural Networks for Image Recognition
Author :
Mendoza, Olivia ; Melin, Patricia ; Licea, Guillermo
Author_Institution :
Univ. Autonoma de Baja California, Tijuana
Abstract :
In this paper we consider a Modular Neural Network combined with two Interval Type-2 Fuzzy Inference Systems (FIS 2) for image recognition. The first FIS 2 is used for edges detection in training data, and the second one to find the best parameters for the Sugeno Integral as decision operator. Once again 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.
Keywords :
decision making; edge detection; fuzzy logic; fuzzy reasoning; image representation; learning (artificial intelligence); neural nets; type theory; Sugeno integral; decision making; edge detection; fuzzy logic; human perception representation; image recognition; interval type-2 fuzzy inference system; modular neural network training; Convolution; Decision making; Detectors; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Image edge detection; Image recognition; Neural networks; Training data;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4371426
