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- W2188162613 abstract "An automated classification of Computerized tomography (CT) images method uses Coiflet wavelets to extract features as input for the classifiers. Support Vector Machine (SVM) module is used to classify the images into different classes. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to optimize the parameters C and gamma of the RBF kernel in SVM. Parameter selection is thought of as an optimization problem where search techniques are used to maximize SVM performance. The observed results are considerably better than the results achieved by employing Support Vector Machine." @default.
- W2188162613 created "2016-06-24" @default.
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- W2188162613 date "2013-01-01" @default.
- W2188162613 modified "2023-09-27" @default.
- W2188162613 title "OPTIMIZING OF SVM FOR CT CLASSIFICATION" @default.
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