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Intermediate results of two state-of-the-art wrapper feature selection approaches (GA and SFFS) associated to a classifier (linear SVM) applied to hyperspectral data sets were used to derive information about band importance for specific land cover classification problems. The impact of the number of selected bands on classification accuracy was obtained thanks to SFFS, while a band importance measure...
This paper presents and evaluates the performance of a method for vehicle detection using a bag-of-features methodology. The algorithm combines Speeded Up Robust Features with a Support Vector Machine. An optimization to the bag-of-features dictionary based on a genetic algorithm for attribute selection is also described. The results obtained show that this method can successfully address the problem...
Fault diagnosis based on the wavelet packet decomposition, one-against-one support vector machine (SVM) and genetic algorithm (GA) is proposed in order to realize the real-time sensor fault diagnosis accurately. The input feature vectors of one-against-one SVM are produced by wavelet packet decomposition of the sensor output signal. GA is used to obtain optimal parameters of one-against-one SVM network...
Building accurate models for video event classification is an important research issue since they are essential components for effective video indexing and retrieval. Recently kernel-based methods, particularly support vector machines, have become popular in multimedia classification tasks. However, in order to use them effectively, several factors that hinder accurate classification results, such...
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