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Depression detection using speech signal is becoming an attractive topic because it is fast, convenient and non-invasive. Many researches aimed at improving depression classification performance. This study investigated application of ensemble learners in depression detection and compared three speaking styles (interview, reading and picture description) in ensembles. A speech dataset collecting from...
A critical task in corner detection in 2D images is on the distinction between a corner pixel and a pixel with a large gradient (i.e., an edge pixel). Imbalanced point detection was proposed to address this problem, where a corner pixel is characterized as a pixel with an imbalanced appearance, while an edge pixel has the opposite property. With extensive experiments, an imbalanced point detector...
Owing to their universal approximation capability and online learning manner, kernel adaptive filters have been widely used in nonlinear systems modeling. Under Gaussian assumption, traditional kernel adaptive algorithms utilize the well-known mean square error(MSE) as a cost function to get optimal solutions. For non-Gaussian situations, MSE will not properly represent the statistics of the error,...
According to the statistics, there is low resource utilization and high energy consumption in traditional servers. To reduce the cost, more and more companies begin to build virtual servers. Sever virtualization implements the mapping from virtual resources to physical resources and deal with resource contention among all VMs. Because of complexity of virtualized server systems, it is necessary to...
The recognition of traffic signs in natural environment is a challenging problem in computer vision because of the influence of weather conditions, illumination, locations, vandalism and other factors. In this paper, we propose a robust traffic signs recognition system for the real utilization of intelligent vehicles. The proposed system is divided into two phases. In the detection and coarse classification...
Smoke detection becomes more and more appealing because of its important application in fire protection. In this paper, we suggest some more universal features, such as the changing unevenness of density distribution and the changing irregularities of the contour of smoke. In order to integrate these features reasonably and gain a low generalization error rate, we propose a support vector machine...
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