Automatic classification of handsegmented image parts with Differential Evolution

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3907 LNCS, Issue , 2006, Pages 403-414

  De Falco, I ^a   Della Cioppa, A ^b   Tarantino, E ^a  

^a CNR   (Italy)

^b UNIVERSITY OF SALERNO   (Italy)

Author keywords

Centroids; Classification; Differential evolution; Multi class database; Recognition of image parts

Indexed keywords

BIT ERROR RATE; CLASSIFICATION (OF INFORMATION); EVOLUTIONARY ALGORITHMS; PROBLEM SOLVING;

CENTROIDS; DIFFERENTIAL EVOLUTION; MULTI-CLASS DATABASE; RECOGNITION OF IMAGE PARTS;

IMAGE SEGMENTATION;

EID: 33745781456     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11732242_36     Document Type: Conference Paper

References (24)

1. Price K, Storn R (1997) Differential evolution. Dr.Dobb's Journal 22(4): 18-24.
2. Storn R, Price K (1997) Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization 11(4):341-359. Kluwer Academic Publishers.
3. Bäck T (1996) Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms. Oxford Univ. Press.
4. Eiben A E, Smith J E (2003) Introduction to evolutionary computing. Springer.
5. Fayyad U M, Piatetsky-Shapiro G, Smyth P, Uthurusamy R (1996) Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press.
6. Duda R O, Hart P E, Stork D G (2001) Pattern Classification. Wiley-Interscience.
7. Weiss S M, Kulikowski G A (1991) Computer Systems that Learn, Classification and Prediciton Methods from Statistics, Neural Networks, Machine Learning and Expert Systems. Morgan Kaufmann, San Mateo, CA.
8. Gomez-Skarmeta A F, Valdes M, Jimenez F, Marin-Blazquez J G (2001) Approximative fuzzy rules approaches for classification with hybrid-GA techniques. Information Sciences 136(1-4):193-214.
9. Luukka P, Sampo J (2004) Weighted Similarity Classifier Using Differential Evolution and Genetic Algorithm in Weight Optimization. Journal of Advanced Computational Intelligence and Intelligent Informatics 8(6):591-598.
10. Paterlini S, Krink T (2004) High Performance Clustering with Differential Evolution. In: Proceedings of the Sixth Congress on Evolutionary Computation (CEC-2004), vol. 2, pp. 2004-2011. IEEE Press, Piscataway NJ.
11. Omran M, Engelbrecht A P, Salman A (2005) Differential Evolution Methods for Unsupervised Image Classification. In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC-2005). IEEE Press, Piscataway NJ.
12. Blake C L, Merz C J (1998) UCI repository of machine learning databases, University of California, Irvine. http://www.ics.uci.edu/~mlearn/MLRepository. html.
13. Piater J H, Riseman E M, Utgoff P E (1999) Interactively training pixel classifiers. International Journal of Pattern Recognition and Artificial Intelligence 13(2): 171-194. World Scientific.
14. Witten I H, Frank E (2000) Data mining: practical machine learning tool and technique with Java implementation. Morgan Kaufmann, San Francisco.
15. Jensen F (1996) An introduction to bayesian networks. UCL Press and Springer-Verlag.
16. Rumelhart D E, Hinton G E, Williams R J (1986) Learning representation by back-propagation errors. Nature 323:533-536.
17. Aha D, Kibler D (1991) Instance-based learning algorithms. Machine Learning 6:37-66.
18. Cleary J G, Trigg L E (1995) K*: an instance-based learner using an entropic distance measure. In: Proceedings of the 12th International Conference on Machine Learning, pp. 108-114.
19. Breiman L (1996) Bagging predictors. Machine Learning 24(2): 123-140.
20. Quinlan R (1993) C4.5: Programs for machine learning. Morgan Kaufmann Publishers, San Mateo, CA.
21. Kohavi R (1996) Scaling up the accuracy of naive-bayes classifiers: a decision tree hybrid. In: Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, pp. 202-207, AAAI Press, Menlo Park, CA.
22. Frank E, Witten I H (1998) Generating accurate rule sets without global optimization. In: Machine Learning: Proceedings of the Fifteenth International Conference, pp. 144-151. Morgan Kaufmann Publishers, San Francisco, CA.
23. Compton P, Jansen R (1988) Knowledge in context: a strategy for expert system maintenance. In: Proceedings of AI'88, pp. 292-306. Springer-Verlag, Berlin.
24. Demiroz G, Guvenir A (1997) Classification by voting feature intervals. In: Proceedings of the 9th European Conference on Machine Learning.