Search results for: S.N. Geethalakshmi

Authors: K. Geethalakshmi, T. Prabhakaran, J. Hemalatha

Abstract:

Nano sized zirconium dioxide in monoclinic phase (m-ZrO2) has been synthesized in pure form through co-precipitation processing at different calcination temperatures and has been characterized by several techniques such as XRD, FT-IR, UV-Vis Spectroscopy and SEM. The dielectric and capacitance values of the pelletized samples have been examined at room temperature as the functions of frequency. The higher dielectric constant value of the sample having larger grain size proves the strong influence of grain size on the dielectric constant.

Keywords: capacitance, dielectric constant, m-ZrO2, nano zirconia

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Authors: N. Valliammal, S.N. Geethalakshmi

Abstract:

This paper describes an optimal approach for feature subset selection to classify the leaves based on Genetic Algorithm (GA) and Kernel Based Principle Component Analysis (KPCA). Due to high complexity in the selection of the optimal features, the classification has become a critical task to analyse the leaf image data. Initially the shape, texture and colour features are extracted from the leaf images. These extracted features are optimized through the separate functioning of GA and KPCA. This approach performs an intersection operation over the subsets obtained from the optimization process. Finally, the most common matching subset is forwarded to train the Support Vector Machine (SVM). Our experimental results successfully prove that the application of GA and KPCA for feature subset selection using SVM as a classifier is computationally effective and improves the accuracy of the classifier.

Keywords: Optimization, Feature extraction, Feature subset, Classification, GA, KPCA, SVM and Computation

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