| Autor: |
Moshou, Dimitrios, De Ketelaere, Bart, Coucke, Peter, De Baerdemaeker, Josse, Ramon, Herman |
| Zdroj: |
IFAC-PapersOnLine; October 1997, Vol. 30 Issue: 26 p125-129, 5p |
| Abstrakt: |
A hierarchical Self-Organizing Map has been developed for solving classification problems, where several measurements have been taken from one object. The algorithm will be used to classify eggs according to their shell state. Broken eggs will be separated from intact eggs. The classification architecture actually consists of two different SOMs. The first SOM clusters the data in an unsupervised way. Afterwards, the ordered activations of each object are collected and fed to the second SOM which assosiates them with a class. This class-vector is assigned to every node in the second map and it is learned with Kohonen's learning rule. |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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