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In this paper, we propose an algorithm called SVM-WKNN for precisely indoor positioning, which can be applied to intelligent robot and wireless sensor network to achieve great performance. The key issue of indoor positioning is how to use the instable wireless network and nonlinear wireless signal strengths to accurately locate the position of a person or object. However, the traditional linear methods,...
The Research of detection malware using machine learning method attracts much attention recent years. However, most of research focused on code analysis which is signature-based or analysis of system call sequence in Linux environment. Obviously, all methods have their strengths and weaknesses. In this paper, we concentrate on detection Trojan horse by operation system information in Windows environment...
Spectral clustering has been used in computer vision successfully in recent years, which refers to the algorithm that the global-optima is found in the relaxed continuous domain obtained by eigendecomposition, and then a multi-class clustering problem should solved by traditional clustering algorithm such as k-means. In this paper, we propose a novel spectral clustering algorithm based on particle...
In real worlds applications, some former research papers have shown that manifold learning tries to discover the non-linear low-dimensional data manifold from a high-dimensional space. Many natural images and the face images are believed to be sampled from a manifold. In this paper, we try to investigate whether discovering such manifold can aid the semi-supervised learning algorithms. We propose...
Complex motion makes consecutive frames experience dramatic change, and thus becomes a barrier to object-tracking. Three factors contribute to more complexity of motion: longer sampling period,an moving object with complex appearance and nonrestraint movement, occlusion, which causes mean shift algorithm losing its target due to too low a Bhattacharyya coefficient. To treat it, mean shift algorithm...
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