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Dictionary generation is a core technique of the bag-of-visual-words (BOV) models when applied to image categorization. Most of previous approaches generate dictionaries by unsupervised clustering techniques, e.g. k-means. However, the features obtained by such kind of dictionaries may not be optimal for image classification. In this paper, we propose a probabilistic model for supervised dictionary...
Vigilance research is very useful and important to our daily lives. EEG has been proved very effective for measuring vigilance. Up to now, many researches mainly focus on using supervised learning methods to analyze the vigilance. However, the labelled information of vigilance is hard to get and sometimes not reliable. In this paper, we proposed a semi-supervised clustering method for vigilance analysis...
Feature selection is a key problem to pattern recognition. So far, most methods of feature selection focus on sample data where class information is available. For sample data without class labels, however, the related methods for feature selection are few. This paper proposes a new way of unsupervised feature selection. Our method is a hybrid approach based on ranking the features according to their...
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