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Recent years have seen significant progress in improving both the efficiency and effectiveness of time series classification. However, because the best solution is typically the Nearest Neighbor algorithm with the relatively expensive Dynamic Time Warping as the distance measure, successful deployments on resource constrained devices remain elusive. Moreover, the recent explosion of interest in wearable...
To properly extract vortex frequencies and improve measurement accuracy of vortex flow meters, the periodogram and Welch based spectral estimation approaches were applied to the analysis of the output signals from a vortex flow meter under various flow rates, and the error characteristics of the two spectral estimation approaches and their performances in different kinds of window functions were discussed...
Moving objects detection is a basic task in video analysis and applications. Many algorithms have been proposed to detect moving objects under different situations in the past decades. In this paper, we propose a new method to detect moving objects in a non-stationary, complex background for an automatic traffic monitoring system. As a pre-treatment, the square neighborhood algorithm is adopted to...
Based on the fact that most of the algorithms assume that the camera is fixed and the changing background is learned in the training period, a robust algorithm is proposed for complex background where a shaking camera, changing background and shadows are presented. It combines a new improved mixture of Gaussians model and a square neighborhood matching algorithm to eliminate shadows and reduce false...
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