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Cross domain data such as numerical or categorical types are ubiquitous in practical network. Network anomaly detection based on cluster analysis exist some difficulties, for example, the initial center of cluster analysis is sensitive and easy to fall into the local optimal solution. Cross domain data involved great information, but can't be effectively used, which will influence the performance...
A new image mosaic algorithm of regional characteristics matching based on fuzzy sets recognition method is presented in this paper. Using shape features such as perimeter, area, flattening and aspect ratio as regional features, introducing fuzzy sets recognition method, it is possible to identify the right matching points. Then image mosaic can be achieved by adopting 8 parameter projection conversion...
In this paper, we introduce a clustering algorithm for intrusion detection based on WaveCluster algorithm and an entropy-based characteristics screening algorithm. WaveCluster algorithm has a low time complexity when the data are low-dimensional, but on the contrary, the actual network data are high-dimensional. So we reduce the dimension of the network data using characteristics screening before...
This paper proposes a novel non-linear dimensionality reduction algorithm, named double-layer isometric feature mapping (DLIso), which generates the trajectories for the video sequence containing different kinds of video clips. First, a nearest neighbor based clustering algorithm is utilized to partition the video sequence into a set of data blocks. Second, intra-cluster graphs are constructed based...
This paper proposes a new face recognition approach by using Independent Component Analysis (ICA) and Ensemble Classifiers based on Support Vector Machine (SVM). Firstly, to improve the quality of the face images, a series of image pre-processing techniques are used. Then the ICA based on Kernel Principal Component Analysis (KPCA) and FastICA is employed to extract features. At last, appropriate classifiers...
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