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Spectral Clustering Algorithms 1.0

  Date Added: April 11, 2013  |  Visits: 353

Spectral Clustering Algorithms

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The code for the spectral graph clustering concepts presented in the following papers is implemented for tutorial purpose:1. Ng, A., Jordan, M., and Weiss, Y. (2002). On spectral clustering: analysis and an algorithm. In T. Dietterich, S. Becker, and Z. Ghahramani (Eds.), Advances in Neural Information Processing Systems 14 (pp. 849 d-deOCt 856). MIT Press.2. P. Perona and W. T. Freeman, "A factorization approach to grouping",In H. Burkardt and B. Neumann, editors, Proc ECCV, pages 655-670, 1998.3. J. Shi and J. Malik, "Normalized Cuts and Image Segmentation", In Proc. IEEE Conf. Computer Vision and Pattern Recognition, pages 731-737, 1997.4. G.L. Scott and H. C. Longuet-Higgins, "Feature Grouping by Relocalisation of Eigenvectors of the Proxmity Matrix", In Proc. British Machine Vision Conference, pages 103-108, 1990.Evolution of spectral clustering methods and the various concepts proposed by the above authors are demonstrated in this implementation.

Requirements: No special requirements
Platforms: Matlab
Keyword: Feature Grouping Longuethiggins Malik Pattern Recognition Scott Vision
Users rating: 0/10

License: Shareware Size: 10 KB
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