Title :
Hybrid SOM and fuzzy integral frameworks for fuzzy classification
Author :
Soria-Frisch, Aureli
Author_Institution :
Dept. Security & Inspection Technol., Fraunhofer IPK, Berlin, Germany
Abstract :
The construction of fuzzy measures in the fuzzy integral, which is considered to be the crucial point for the extended utilization of this fusion methodology, is attained in the here presented paper through a Self-Organizing Map (SOM). This fact can improve the performance in the fuzzy measure assessment specially in high-dimensional feature spaces. Different methodologies for knowledge discovery related to the SOM paradigm are taken into consideration in order to achieve the assessment of the fuzzy measure coefficients. Furthermore an overview of the utilization of the fuzzy integral in classification problems is given. Finally two hybrid frameworks considering the SOM and the fuzzy integral are presented and used for fuzzy classification.
Keywords :
fuzzy neural nets; fuzzy set theory; integral equations; pattern classification; self-organising feature maps; crucial point; fusion methodology; fuzzy classification problem; fuzzy integral frameworks; fuzzy measure assessment; fuzzy measure coefficients; fuzzy neural nets; fuzzy stet theory; fuzzy systems; high dimensional feature spaces; hybrid SOM; hybrid frameworks; neurons; self organizing map; Area measurement; Extraterrestrial measurements; Fuzzy systems; Gabor filters; Humans; Image analysis; Image texture analysis; Inspection; Paper technology; Security;
Conference_Titel :
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN :
0-7803-7810-5
DOI :
10.1109/FUZZ.2003.1206539