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26 articles for “Kernel Methods”
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Research ArticleOpen accessIn the abstractEnhanced Support Vector Machine based on Metaheuristic Search for Multiclass ProblemsAbdullah Saeed Ghareb, Mohammed Hamid Afif, Abdel-Rahman Hedar et al.Machine learning is an important field of artificial intelligent researches and it highly growing for real intelligent applications systems that relate brain computer interface to human brain activities. Support Vector Machine (SVM) is a popular machine learning approach, which can be used for pattern recognition, prediction and classification with many diverse applications. However, the SVM has many parameters, which have … …Journal of Computer Science, Vol. 16, Issue 7 · 9 Jul 2020 · 6,906 accessesView PDFCite
Research ArticleOpen accessIn the abstractDirect Sequence and Frequency Hopping Signals Classification Based on Co-Occurrence Matrix and Clustering TechniquesHaidy S. Fouad, Hend A. Elsayed, Shawkat K. GirgisSpread Spectrum techniques (SS) were first developed for military applications, but currently, they have commercial applications. SS provides secure communication and allows multiple accesses for same radio spectrum. So, most Wireless Local Area Network (WLAN) systems use it, as do Cognitive Radios (CR), space systems and Global Positioning Systems (GPS). Direct Sequence Spread Spectrum (DSSS) and frequency hopped spread spectrum … …Journal of Computer Science, Vol. 15, Issue 1 · 10 Jan 2019 · 8,203 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetermination of SVM-RBF Kernel Space Parameter to Optimize Accuracy Value of Indonesian Batik Images ClassificationAvinanta Tarigan, Dewi Agushinta, Adang Suhendra, Fikri BudimanImage retrieval using Support Vector Machine (SVM) classification verydepends on kernel function and parameter. Kernel function used by dot productsubstitution from old dimension feature to new dimension depends on imagedataset condition. In this research, parameter of Gaussian /Radial BasisFunction (RBF) kernel function is optimized using multi class non-linear SVMmethod and implemented to training and test datasets of traditional Indonesian batik … …Journal of Computer Science, Vol. 13, Issue 11 · 23 Oct 2017 · 7,530 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Feature Extraction Method for Accuracy Improvement in “Aksara Lontara” TranslationIntan Sari Areni, Asyraful Insan Asry, IndrabayuAn Optical Character Recognition (OCR) of “Aksara Lontara” has been constructed using a novel combination of feature extraction methods in this study. The ancient font of “Lontara” is then translated into Bahasa Indonesia to help non-native language to learn this language. Two powerful extraction feature methods, i.e., Modified Direction Feature (MDF) and Fourier Descriptor (FD) are stages combined to deal … …Journal of Computer Science, Vol. 13, Issue 9 · 27 Aug 2017 · 8,851 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization of Penalty Parameter in Penalized Nonlinear Canonical Correlation Analysis by using Cross-ValidationIsamu NagaiThere is Canonical Correlation Analysis (CCA) as a way to find a linear relationship between a pair of random vectors. However, CCA cannot find a nonlinear relationship between them since the method maximizes the correlation between linear combinations of the vectors. In order to find the nonlinear relationship, we convert the vectors through some known conversion functions like a kernel … …Journal of Mathematics and Statistics, Vol. 11, Issue 3 · 22 Dec 2015 · 7,661 accessesView PDFCite
Research ArticleOpen accessIn the abstractNATURAL ANTIOXIDANT INGREDIENT FROM BY-PRODUCTS OF FRUITSG. S. El-Baroty, M. F. Khalil, S. H.A. MostafaThe contents of total phenolics compounds and their phenolic constituents were quantified in organic and aqueous of four varieties (Zebdia, Sukkari, taimor and Hindi) of mango (Mangifera indica L.), seeds pulp and kernel, one varieties of pomegranate (Punica ranatum L., peel) and peanut (Arachis hypogaea L., Giza 6, shell) by-products. The antioxidant activities of all by products extracts were assessed … …American Journal of Agricultural and Biological Sciences, Vol. 9, Issue 3 · 22 Mar 2014 · 8,170 accessesView PDFCite
Research ArticleOpen accessIn the abstractHYPERPARAMETER SELECTION IN KERNEL PRINCIPAL COMPONENT ANALYSISMd. Ashad Alam, Kenji FukumizuIn kernel methods, choosing a suitable kernel is indispensable for favorable results. No well-founded methods, however, have been established in general for unsupervised learning. We focus on kernel Principal Component Analysis (kernel PCA), which is a nonlinear extension of principal component analysis and has been used electively for extracting nonlinear features and reducing dimensionality. As a kernel method, kernel PCA … …Journal of Computer Science, Vol. 10, Issue 7 · 15 Feb 2014 · 8,721 accessesView PDFCite
Research ArticleOpen accessIn the abstractEffect of Complete Micro Nutrient Fertilizer Application on Soybean Yield and Yield ComponentsFarimah Ghannadi Behrouzi, Sardar Germchi, Mehrdad YarniaIn last decades, sever population growth cause to enormous problems in developing countries. One of the effective factors in improving of quantity and quality of agricultural products is optimal application of chemical fertilizers. Hence, any research in this field can be an effective step to decrease production costs and increase productivity. In order to evaluation effects of complete micro nutrient … …American Journal of Agricultural and Biological Sciences, Vol. 7, Issue 4 · 5 Oct 2012 · 8,127 accessesView PDFCite
Research ArticleOpen accessIn the abstractPecan Weevil Recognition Using Support Vector Machine MethodGhulam Mubashar Hassan, Saleh Mufleh Al-SaqerProblem statement: The Pecan weevil was considered as the most dangerous pest of Pecan fruits. The aim of this research is to evaluate Support Vector Machine method (SVM) for identifying Pecan Weevil among other insects. Eventually, this recognition system will serve in a wireless imaging network for monitoring Pecan Weevils. Approach: SVM has been evaluated using two different kernel functions … …American Journal of Agricultural and Biological Sciences, Vol. 6, Issue 4 · 24 Dec 2011 · 7,926 accessesView PDFCite
Research ArticleOpen accessIn the abstractBoosting Kernel Discriminative Common Vectors for Face RecognitionC. Lakshmi, M. PonnavaikkoProblem statement: Kernel discriminative common vector (KDCV) was one of the most effective non-linear techniques for feature extraction from high dimensional data including images and text data. Approach: This study presented a new algorithm called Boosting Kernel Discriminative Common Vector (BKDCV) to further improve the overall performance of KDCV by integrating the boosting and KDCV techniques. Results: In BKDCV, the … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,571 accessesView PDFCite