Introduction to Pattern Recognition: A Matlab Approach

Introduction to Pattern Recognition: A Matlab Approach

Volumn , Issue , 2010, Pages 1-219

  Theodoridis, Sergios ^a,b   Pikrakis, Aggelos ^c   Koutroumbas, Konstantinos ^d   Cavouras, Dionisis ^e  

^a UNIVERSITY OF ATHENS   (Greece)

^b THE CHINESE UNIVERSITY OF HONG KONG   (China)

^c UNIVERSITY OF PIRAEUS   (Greece)

^d NATIONAL OBSERVATORY OF ATHENS   (Greece)

^e NONE

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85147072507     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1016/C2009-0-18558-6     Document Type: Book

References (8)

1. J. Boberg and T. Salakoski (1993) General formulation and evaluation of agglomerative clustering methods with metric and non-metric distances. Pattern Recognition Vol. 26(9), 1395-1406.
2. S. Guattery and G.L. Miller (1998) On the quality of spectral separators. SIAM Journal of Matrix Analysis and Applications Vol. 19(3), 701-719.
3. S.S. Keerthi, S.K. Shevade, C. Bhattacharyya and K.R.K. Murthy (2001) Improvements to Platt's SMO Algorithm for SVM Classifier Design. Neural Computation Vol. 13(3), 637-649.
4. U. Luxburg (2007) A tutorial on Spectral Clustering. Statistics and Computing Vol. 17(4), 395-416.
5. D. Mease and A. Wyner (2008) Evidence contrary to the statistical view of boosting. Journal of Machine Learning Research Vol. 9 131-156.
6. M. Petrou and P.G. Sevilla (2006) Image Processing: Dealing with Texture John Wiley & Sons
7. J. Shi and J. Malik (2000) Normalized cuts and edge segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 22(8), 888-905.
8. S. Theodoridis and K. Koutroumbas (2009) Pattern Recognition 4th ed. Academic Press