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A single feature extractor-classifier is not usually able to deal with the diversity of multiple image scenarios. Therefore, integration of features and classifiers can bring benefits to cope with this problem, particularly when the parts are carefully chosen and synergistically combined. In this paper, we address the problem of pedestrian detection by a novel ensemble method. Initially, histograms...
Abstract-Brain Computer Interface (BCI) systems based on electroencephalography (EEG) open a new communication channel for people with severe motor disabilities, without recurring to the conventional motor output pathways. The very low signal-to-noise ratio and low spatial resolution still limits severely BCIs communication bandwidth. This paper presents the ongoing work toward the development of...
Spatial filtering is an important technique used in electroencephalography to enhance signal-to-noise ratio and to reduce the data dimensionality. In the context of Brain-Computer Interfaces, the Common Spatial Patterns method is widely used for classification of motor imagery events, however it is not very often used for classification of event related potentials such as P300. In this paper we show...
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