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This paper presents a method for detecting people from images taken with a camera mounted on a robot. The purpose of the detection is avoiding people collision while robot is moving within an unknown environment. It combines two algorithms for this purpose. First, the appearance of people is learned using a set of Haar-like features and the Adaboost algorithm. This information is embedded by building...
The paper proposed an object tracking framework based on Adaboost and mean-shift for image sequence. The object rectangle and scene rectangle in the initial image of the sequence were drawn and then, labeled the pixel data in the two rectangles with 1 and 0. Trained the Adaboost classifier by the pixel data and the corresponding labels. The obtained classifier was improved to be a 5 class classifier...
Discovery of the image voxels of the brain that represent real activity is, in general, very difficult because of a weak signal-to-noise ratio and the presence of artifacts. The first tests of the classical data mining algorithms in this field showed low performances and weak quality of recognition. In this article, a new interactive data-driven approach to functional magnetic resonance imagery mining...
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