1. Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology 1 Growing Mechanisms and Cluster Identification with TurSOM Presenter : Jun-Yi Wu Authors : Derek Beaton, Iren Valova, Dan MacLean 2009 IJCNN

2. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 2 Motivation  The traditional SOM is slower than TurSOM and need for post-processing methods for cluster identification.  The traditional Growth network has some problems, (e.g Growing Neural Gas, Growing Cells, and Growing Grids, ESOINN, ParaSOM)

3. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Objectives 3  To purpose new features of TurSOM adding to the robustness and effectiveness as a clustering or image segmentation method.  To eliminate post-processing techniques that are used for severing SOM networks to determine clusters or classes.  TO improve the disadvantages of growing network.

4. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 4  TurSOM A. Neurons B. Connections  Growing Mechanisms  Pruning

5. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 5  TurSOM A. Neurons B. Connections

6. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 6  Growing Mechanisms

7. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 7  Pruning  To ensure that no excessive growth, or over-fitting, resulting in poor representation of the input.  The pruning mechanism of TurSOM occurs between one dimensional convergence, and two-dimensional growth.

8. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 8 A. Gray scale portrait B. Structural MRI A B Magnetic resonance imaging

9. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 9 Gray scale portrait

10. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 10 Gray scale portrait

11. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 11 Structural MRI

12. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 12 Structural MRI

13. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 13 Structural MRI

14. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 14 Structural MRI

15. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 15 Conclusions  TurSOM is a powerful, robust and efficient variant of the SOM algorithm.  Growing mechanisms applied to TurSOM, enhance the standard one dimensional capability of TurSOM.

16. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 16 Comments  Advantages ─ According to previous experiments show that the effective use of the image segmentation.  Applications ─ Pattern Recognition