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In the Brain-computer interface, classification and recognition technology plays an important role, especially the EEG classification and recognition for the movement imagery. In this paper, we use a new type of sensors to collect EEG signals. According to imagine the movement of left or right hand to identify two types of thinking, we proposed a new recognition method based on AR(auto-regressive)...
In this paper we propose a novel framework for action recognition based on multiple features for improve action recognition in videos. The fusion of multiple features is important for recognizing actions as often a single feature based representation is not enough to capture the imaging variations (view-point, illumination etc.) and attributes of individuals (size, age, gender etc.). Hence, we use...
Color-to-gray is a classical manipulation in image processing. In this paper, a kernel based method is presented to carry out color-to-gray operation. It is noticeable that, in a meaningful color image only the linear combination of the three color components of every pixel is hardly enough to describe the implication relation between the luminance and chrominance in every pixel, or between pixels...
We propose an algorithm for extracting fields from HTML search results. The output of the algorithm is a database table - a data structure that better lends itself to high-level data mining and information exploitation. Our algorithm effectively combines tree and string alignment algorithms, as well as domain-specific feature extraction to match semantically related data across search results. The...
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