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67 articles for “Mixture model”
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Research ArticleOpen accessPhrase in the titleAn Ensemble of Gaussian Mixture Model and Support Vector Machines for Network Intrusion DetectionOlujimi Daniel Alao, Sheriff Alimi, Shade Oluwakemi Kuyoro et al.NetworkIntrusion Detection Systems (NIDS) can protect computer networks and computersystems by detecting abnormal network packets and taking agreed action plans,such as notifying an administrator or rejecting the network packets. In this study,the aim is the implementation of NIDS with improved performance using anensemble of Support Vector Machines (SVMs) and the Gaussian Mixture Model(GMM). Four SVMs with Radial Basis Function (RBF), … …Journal of Computer Science, Vol. 18, Issue 9 · 21 Sep 2022 · 6,114 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleMultiple Vehicle Tracking using Adaptive Gaussian Mixture Model and Kalman FilterFandy Setyo UtomoBased on data from the Central Statistics Agency (BPS) of the Republic of Indonesia in catalog Crime Statistics in 2014, the number of crimes of theft of motor vehicles has increased since 2010 until 2013. Recorded in 2013 the number reached 42.508 cases of theft. In this study, we made a prototype application using Adaptive Gaussian Mixture Models algorithms and … …American Journal of Applied Sciences, Vol. 13, Issue 12 · 22 Dec 2016 · 7,375 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePARALLEL IMPLEMENTATION OF EXPECTATION-MAXIMISATION ALGORITHM FOR THE TRAINING OF GAUSSIAN MIXTURE MODELSG. F. Araújo, H. T. Macedo, M. T. Chella et al.Most machine learning algorithms need to handle large data sets. This feature often leads to limitations on processing time and memory. The Expectation-Maximization (EM) is one of such algorithms, which is used to train one of the most commonly used parametric statistical models, the Gaussian Mixture Models (GMM). All steps of the algorithm are potentially parallelizable once they iterate over … …Journal of Computer Science, Vol. 10, Issue 10 · 9 Jul 2014 · 6,937 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleGAUSSIAN MIXTURE MODEL BASED CLASSIFICATION OF MICROCALCIFICATION IN MAMMOGRAMS USING DYADIC WAVELET TRANSFORMSuman Mishra, Hariharan RanganathanBreast cancer is a serious health related issue for women in the world. Cancer detected at premature stages has a higher probability of being cured, whereas at advanced stages chances of survival are bleak. Screening programs aid in detecting potential breast cancer at early stages of the disease. Among the various screening programs, mammography is the proven standard for screening … …Journal of Computer Science, Vol. 9, Issue 10 · 5 Sep 2013 · 6,867 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA New Modified Gaussian Mixture Model for Color-Texture SegmentationM. Sujaritha, S. AnnaduraiProblem statement: This study presents a new, simple and efficient modified Gaussian mixture model based clustering algorithm for color-texture segmentation. The proposed mixture model introduces a new component density function which incorporates spatial information and the weighting factor for neighborhood effect is fully adaptive to the image content. Approach: It enhances the smoothness towards piecewise-homogeneous segmentation and reduces the edge-blurring … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,329 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAn Accurate Mango Pest Identification Employing the Gaussian Mixture Model and Expectation-Maximization (EM) AlgorithmD. Lita Pansy, M. MuraliMangoes are fruits that originated in South and Southeast Asia. Mango fruits are consumed in high volume worldwide. However, fruit, stem, root, and mango leaves are damaged by pests, and it has a significant negative impact on mango production. Many works were developed for the pest detection of mango; but, none of the works concentrated on the practical applicability and … …Journal of Computer Science, Vol. 21, Issue 1 · 3 Dec 2024 · 5,063 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAn Algorithm for Determining the Number of Mixture Components on the Bayesian Mixture Model Averaging for Microarray DataAni Budi Astuti, Nur Iriawan, Irhamah, Heri KuswantoThe major challenges on the statistical analysis of microarray data are the limited availability of samples, large number of measured variables and the complexity of distribution of the data obtained (e.g., multimodal). These phenomena could be considered in Bayesian method, used Bayesian Mixture Model (BMM) methods and Bayesian Model Averaging (BMA) methods. Modeling of Bayesian Mixture Model Averaging (BMMA) for … …Journal of Mathematics and Statistics, Vol. 11, Issue 2 · 28 Sep 2015 · 7,136 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA GAUSSIAN MIXTURE MODEL FOR CLASSIFYING THE HUMAN AGE USING DWT AND SAMMON MAPJ. Nithyashri, G. KulanthaivelThe appearance of a human face rigorously changes with respect to age that makes Age Classification as a more challenging task. The algorithms such as, K-Nearest Neighbor (K-NN), Support Vector Machine (SVM), Radial Basis Function (RBF), motivated many Face Researchers to focus their attention in classifying the human age into various age groups. The Classification rate produced by these existing … …Journal of Computer Science, Vol. 10, Issue 11 · 20 Dec 2014 · 7,707 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Note on Model Selection in Mixture ExperimentsKadri Ulaş AkayIn mixture experiments, determination of the best model for modeling the mixture system is significant in both understanding and interpreting the system. For obtaining the best model in mixture experiments, different methods have been used. Most commonly used methods are the stepwise type methods. However, the models obtained with these methods are not always the best model depending on the … …Journal of Mathematics and Statistics, Vol. 3, Issue 3 · 30 Sep 2007 · 6,939 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMultivariate Option Pricing with Gaussian Mixture Distributions and Mixed CopulasJimbo Henri Claver, Tatanfack Emerson, Shu FelixRecently, it has been reported that the hypothesis proposed by the classical black scholes model to price multivariate options in finance were unrealistic, as such, several other methods have been introduced over the last decades including the copulas methods which uses copulas functions to model the dependence structure of underlying assets. However, the previous work did not take into account … …Journal of Mathematics and Statistics, Vol. 19, Issue 1 · 3 Apr 2023 · 6,511 accessesView PDFCite