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In order to meet the requirements of traffic data fusion for real-time urban traffic state estimation, a new kind of fusion structure model is proposed. This fusion model consists of both spatial fusion and temporal fusion. First we use the power average operator as spatial fusion method. Then we propose a temporal correlation based data compression (TCDC) algorithm, based on segment linear regression...
In this study, we propose a novel solution to regulate the amount of interest points extracted from an image without significant additional computational cost. Our method acts at the very beginning of the detection process by using a corner occurrence model in order to predict the optimal threshold for a user-defined number of detections. Compared to existing approaches which guarantee a reasonable...
In a distributed computing environment, peers collaboratively learn to classify concepts of interest from each other. When external changes happen and their concepts drift, the peers should adapt to avoid increase in misclassification errors. The problem of adaptation becomes more difficult when the changes are asynchronous, i.e., when peers experience drifts at different times. We address this problem...
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