Support Vector Machine Applied to Compress Medical Image

Rule-Based Support Vector Machine Classifiers Applied to Tornado Prediction

A rule-based Support Vector Machine (SVM) classifier is applied to tornado prediction. Twenty rules based on the National Severe Storms Laboratory’s mesoscale detection algorithm are used along with SVM to develop a hybrid forecast system for the discrimination of tornadic from nontornadic events. The use of the Weather Surveillance Radar 1998 Doppler data, with continuous data streaming in eve...

Support Vector Machine Classiiers as Applied to Aviris Data

Traditionally, classi ers model the underlying density of the various classes and then nd a separating surface. However density estimation in high-dimensional spaces su ers from the Hughes e ect (Hughes, 1968), (Landgrebe, 1999): For a xed amount of training data the classi cation accuracy as a function of number of bands reaches a maximum and then declines, because there is limited amount of t...

Evolutionary Support Vector Machine for Parameters Optimization Applied to Medical Diagnostic

The parameter selection is very important for successful modelling of input–output relationship in a function classification model. In this study, support vector machine (SVM) has been used as a function classification tool for accurate segregation and genetic algorithm (GA) has been utilised for optimisation of the parameters of the SVM model. Having as input only five selected features, param...

Support Vector Machine for Automatic Image Annotation

Automatic image annotation (AIA) is an active topic of research in computer vision and pattern recognition. In the last two decades, large amount of researches on AIA have been proposed, mainly including classification-based methods and probabilistic modeling methods. As one of the most common methods for AIA, support vector machine (SVM) has been widely applied in the multimedia research commu...

Contextual image classification with Support Vector Machine