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MC-SC2 Publications about: pattern recognition
Articles in journal or book chapters
  1. A. Salappa, M. Doumpos, and C. Zopounidis. Feature selection algorithms in classification problems: An experimental evaluation. Foundations of Computing and Decision Sciences, 30(4):331-349, 2005. Keyword(s): feature selecion, pattern recognition, decision analysis, performance evaluation. [bibtex-entry]

  2. H. Schneiderman and T. Kanade. Object Detection Using the Statistics of Parts. International Journal of Computer Vision, 56(3):151-177, 2004. Keyword(s): object recognition, object detection, face detection, car detection, pattern recognition, machine learning, statistics, computer vision, wavelets, classification. [bibtex-entry]

  3. W.-J. Wang, Y.-X. Tan, J.-H. Jiang, J.-Z. Lu, G.-L. Shen, and R.-Q. Yu. Clustering based on kernel density estimation: nearest local maximum searching algorithm. Chemometrics and Intelligent Laboratory Systems, 72(1):1-8, 2004. Keyword(s): NLMSA, pattern recognition, cluster analysis, kernel density estimation, local optimization. [bibtex-entry]

  4. J. DeVinney and J. Wierman. A SLLN for a one-dimensional class cover problem. Statistics & Probability Letters, 59:425-435, 2002. Keyword(s): class cover problem, catch disgraphs, domination, poisson process, complete convergence, strong law of large numbers, classification, pattern recognition. [bibtex-entry]

  5. J. Mandziuk and L. Shastri. Incremental class learning approach and its application to handwritten digit recognition. Information Sciences: An International Journal, 141:193-217, 2002. Keyword(s): incremental class learning, catastroghic interference problem, supervised learning, spatio-temporal representation, pattern recognition, handwritten digit recognition, neural networks. [bibtex-entry]

  6. S. Bermejo and J. Cabestany. Oriented principal component analysis for large margin classifiers. Neural Networks, 14:1447-1461, 2001. Keyword(s): large margin classifiers, oriented principal component analysis, co-operative learning, principal componet neural networks, learning-to-learn algorithms, feature extraction, online gradient descent, pattern recognition. [bibtex-entry]

  7. M. Pardo, G. Sberveglieri, A. Taroni, F. Masulli, and G. Valentini. Decompositive classification models for Electronic Noses. Analytica Chimica Acta, 446:223-232, 2001. Keyword(s): pattern recognition, ensemble methods, classification tree, output coding, multilayer perception, electronic nose. [bibtex-entry]

  8. M. Pardo, G. Sberveglieri, S. Gardini, and E. Dalcanale. A hierarchical classification scheme for an Electronic Nose. Sensors and Actuators B: Chemical, 69:359-365, 2000. Keyword(s): hierarchical classification, pattern recognition, ANN, Simca, electronic nose. [bibtex-entry]

  9. Y. Li, J.-H. Jiang, Z.-P. Chen, C.-J. Xu, and R.-Q. Yu. A new method based on counterpropagation network algorithm for chemical pattern recognition. Analytica Chimica Acta, 388:161-170, 1999. Keyword(s): pattern recognition, counterpropagation network (CPN), standard linear discriminant analysis (SLDA), backpropagation network (BPN). [bibtex-entry]

  10. Y.-H. Liu and J. Dauer. Bicriteria programming with several modern applications. Computers & Industrial Engineering, 37(3):563-580, 1999. Keyword(s): bicriteria programming, genotype selection, pattern recognition, multicriteria optimization. [bibtex-entry]

  11. R. Östermark. A fuzzy neural network algorithm for multigroup classification. Fuzzy Sets and Systems, 105(1):113-122, 1999. Keyword(s): artificial intelligence, multicriteria analysis, pattern recognition, hybrid fuzzy neural networks, Fuzzy set theory, multigroup classification. [bibtex-entry]

  12. S. Kundu and A. Martinsek. Using a stopping rule to determine the size of the training sample in a classification problem. Statistics & Probability Letters, 37:19-27, 1998. Keyword(s): classification, discrimination, pattern recognition, density estimate, stopping rule. [bibtex-entry]

  13. N. Maglaveras, T. Stamkopoulos, K. Diamantaras, C. Papas, and M. Strintzis. ECG pattern recognition and classification using non-linear transformations and neural networks: A review. International Journal of Medical Informatics, 52:191-208, 1998. Keyword(s): biomedical signal processing, ECG processing, non-linear principal component analysis, neural networks, ischemia detection. [bibtex-entry]

  14. H. Ishibuchi, T. Murata, and I. Türksen. Single-objective and two-objective genetic algorithms for selecting linguistic rules for pattern classification problems. Fuzzy Sets and Systems, 89(2):135-150, 1997. Keyword(s): linguistic modeling, pattern recognition, data analysis, genetic algorithm, rule selection. [bibtex-entry]

  15. S. Olariu and N. Rao. Simple algoritms for some classification problems. Pattern Recognition Letters, 17:163-167, 1996. Keyword(s): classification, pattern recognition, partitions, equivalence relations, refinement. [bibtex-entry]



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Last modified: Fri Dec 15 07:05:48 2006
Author: Juscelino Dias.

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