PATTERN RECOGNITION OF METEOROLOGICAL FIELDS CAUSING HEAVY RAINFALL DISASTER IN HIROSHIMA USING SELF-ORGANIZING MAP

2019 ◽  
Vol 75 (2) ◽  
pp. I_1201-I_1206
Author(s):  
Koji NISHIYAMA ◽  
Izumi YOKOTA ◽  
Yoshinari HIROSHIRO ◽  
Koji ASAI
Keyword(s):  
Pattern Recognition ◽  
Heavy Rainfall ◽  
Self Organizing Map ◽  
Self Organizing

Identification of typical synoptic patterns causing heavy rainfall in the rainy season in Japan by a Self-Organizing Map

2007 ◽  
Vol 83 (2-4) ◽  
pp. 185-200 ◽  
Author(s):  
Koji Nishiyama ◽  
Shinichi Endo ◽  
Kenji Jinno ◽  
Cintia Bertacchi Uvo ◽  
Jonas Olsson ◽  
...  
Keyword(s):  
Rainy Season ◽  
Heavy Rainfall ◽  
Self Organizing Map ◽  
Synoptic Patterns ◽  
Self Organizing

Self-Organizing Map Application for Iris Recognition

2014 ◽  
Vol 3 (2) ◽  
pp. 10
Author(s):  
Anna Sedrak Hovakimyan ◽  
Siranush Gegham Sargsyan ◽  
Arshak Nazaryan
Keyword(s):  
Pattern Recognition ◽  
Problem Solving ◽  
Iris Recognition ◽  
Classification Problem ◽  
Self Organizing Map ◽  
Self Organizing Maps ◽  
The Neural Network ◽  
Human Iris ◽  
Iris Patterns ◽  
Self Organizing

Human iris is  a good subject of biometrical identification, since  iris patterns are unique like fingerprints. Iris is well protected against damage, unlike fingerprints, which can be harder to recognize after years of certain types of manual labor.A problem of iris recognition is considered in the paper. In machine learning, pattern recognition is the assignment of a label to a given input value. Pattern classification is an example of pattern recognition: it attempts to assign each input value to one of a given set of classes. Nowadays various techniques are used for this purpose, and in particular artificial neural networks.For iris recognition problem solving  Kohenen Self Organizing Maps are suggested to use. The software for iris recognition is developed  which is customizable and allows to select the appropriate parameters of the neural network to obtain the most satisfactory results. The developed Self-Organizing Map Library of classes can be used for various kinds of object classification problem solving as well as for any problems suitable to solve with Self-Organizing Maps.

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