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Brain-computer interface (BCI) plays an important role in helping the people with severe motor disability. In event-related potential (ERP) based BCIs, subjects were asked to count the target stimulus in the offline experiment, the recorded electroencephalogram (EEG) data was used to train the classification mode. However, subjects may make mistakes in counting the target stimulus or be affected by...
In order to obtain the higher classification accuracy in specific categories for the different feature subset, a hierarchical classification algorithm based on Feature Selection is proposed, and is used for synthetic aperture radar (SAR) image classification, and feature selection is achieved by Genetic algorithm. The algorithm has two main characteristics: one is hierarchical classification which...
Aim at the problems of low classification accuracy rate of the traditional single feature and the multi-features dimension disaster, a ensemble learning algorithm based on multi-features fusion and selection is proposed, and is used for polarimetric SAR image classification. Firstly, various features of SAR image is extracted and fused by normalized; then, different feature selection methods are used...
In this paper, we propose a novel approach to identifying user intents of search engine queries. Specifically, we recast it as a classification problem, in which four types of features are adopted. The classification features are based on deep linguistic analysis of queries as well as search engine feedbacks. We evaluate the method with the real web query data. The results show that about 88% of the...
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