Gaussian mixture model application de kumar vignesh (3 resultados)
- Tapa blanda
Librería: Revaluation Books, Exeter, , Reino UnidoRevaluation Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 67,85
Envío por EUR 11,59Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: Brand New. 8.70x6.02x0.28 inches. In Stock.
- Tapa blanda
Librería: Buchpark, Trebbin, , AlemaniaBuchpark
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado
EUR 19,36
Envío por EUR 105,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: Hervorragend. Zustand: Hervorragend | Seiten: 56 | Sprache: Englisch | Produktart: Bücher | Gaussian Mixture Model (GMM) is the probabilistic model, it works well with the classification and parameter estimation strategy. In this Maximum Likelihood Estimation (MLE) based on Expectation Maximization (EM) is being used…for the parameter estimation approach and the estimated parameters are being used for the training and the testing of the images for their normality and the abnormality. With the mean and the covariance calculated as the parameters they are used in the Gaussian Mixture Model (GMM) based training of the classifier. Support Vector Machine a discriminative classifier and the Gaussian Mixture Model a generative model classifier are the two most popular techniques used in this work. The performance of the classification strategy of both the classifiers used have a better proficiency when compared to the other classifiers. By combining the SVM and GMM we could be able to classify at a better level since estimating the parameters through the GMM has a very few amount of features and hence it is not needed to use any of the feature reduction techniques.
- Tapa blanda
- Impresión bajo demanda
Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 40,89
Envío por EUR 60,51Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Gaussian Mixture Model (GMM) is the probabilistic model, it works well with the classification and parameter estimation strategy. In this Maximum Likelihood Estimation (MLE) based on Expectation Maximization (EM) is being used for the pa…rameter estimation approach and the estimated parameters are being used for the training and the testing of the images for their normality and the abnormality. With the mean and the covariance calculated as the parameters they are used in the Gaussian Mixture Model (GMM) based training of the classifier. Support Vector Machine a discriminative classifier and the Gaussian Mixture Model a generative model classifier are the two most popular techniques used in this work. The performance of the classification strategy of both the classifiers used have a better proficiency when compared to the other classifiers. By combining the SVM and GMM we could be able to classify at a better level since estimating the parameters through the GMM has a very few amount of features and hence it is not needed to use any of the feature reduction techniques.
