scholarly journals The New Architecture of Simplified Fuzzy ARTMAP for Supporting Medical Diagnostic Reasoning

2013 ◽  
Vol 81 (17) ◽  
pp. 16-19
Author(s):  
Pranamika Kakati ◽  
Hemanta K. Baruah
2014 ◽  
Vol 22 ◽  
pp. 101-107 ◽  
Author(s):  
Jeonghyun Baek ◽  
Heesung Lee ◽  
Byungyun Lee ◽  
Heejin Lee ◽  
Euntai Kim

Author(s):  
S. RAJASEKARAN ◽  
G. A. VIJAYALAKSHMI PAI

The capability of Kasuba's Simplified Fuzzy ARTMAP (SFAM) to behave as a Pattern Recognizer/Classifier of images both noisy and noise free has been investigated in this paper. This calls for augmenting the original Neuro–Fuzzy model with a modified moment-based RST invariant feature extractor. The potential of the SFAM based Pattern Recognizer to recognize patterns — monochrome and color, noisy and noise free — has been studied on two experimental problems. The first experiment which concerns monochrome images, pertains to recognition of satellite images, a problem discussed by Wang et al. The second experiment, which concerns color images, deals with the recognition of some sample test colored patterns. The results of the computer simulation have also been presented.


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