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Your search keyword '"Ning, Jifeng"' showing total 23 results
Start Over Author "Ning, Jifeng" Publisher elsevier bv
23 results on '"Ning, Jifeng"'

17. Cost-sensitive learning for social network analysis and network measurement

Author

Meili Wang, Ning Jifeng, Zhang Xing, and Zhang Yang

Subjects
General Computer Science, Computer science, business.industry, Cost sensitive, Estimator, Pattern recognition, 02 engineering and technology, Machine learning, computer.software_genre, ComputingMethodologies_PATTERNRECOGNITION, Control and Systems Engineering, 020204 information systems, Network measurement, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Artificial intelligence, Electrical and Electronic Engineering, Unbalanced data, business, computer, Classifier (UML)
Abstract

Recently, the application of data mining techniques to social network analysis and network measurement has received considerable attention. In this work, an aggregating N-dependence estimator (ANDE)-based cost-sensitive classification algorithm (CS_ANDE) was proposed for use with the unbalanced data commonly observed in social networks and network measurements. First, a one-dependence estimator was adopted to determine the approximate cost of misclassification. Second, multiple classifiers were constructed to minimize the misclassification cost. Subsequently, these classifiers were used to re-label samples. Ultimately, a CS_AODE classifier was obtained by learning these re-labeled samples. Consistent with two-dependence estimators, a CS_A2DE classifier was acquired. The CS_AODE and CS_A2DE classifiers were empirically evaluated against MetaCost and AODE for UCI datasets, and the results indicated that CS_AODE and CS_A2DE significantly outperformed the other classifiers and that the performance was stable under different parameters.

Published
2017
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21. NGVF: An improved external force field for active contour model

Author

Wu Chengke, Liu Shi-Gang, Ning Jifeng, and Yang ShuQin

Subjects
Active contour model, Tangent, Image processing, Geometry, Edge detection, Diffusion process, Rate of convergence, Artificial Intelligence, Signal Processing, Image scaling, Computer Vision and Pattern Recognition, Normal, Software, Mathematics
Abstract

An improved external force field for active contour model, called as NGVF, is presented in this paper. Based on analyzing the diffusion process of the GVF and three interpolation functions, it is found that the generation of GVF contains diffusions in two orthogonal directions along the edge of image, one is the tangent direction and the other is the normal direction. Moreover, the diffusion in the normal direction plays the key role on the diffusion of GVF, while the diffusion in the tangent direction has little effect. So the GVF in the normal direction (NGVF) is taken as a new force field to study. Experiment results with several test images reveal that, compared with GVF, NGVF can enter into long, thin indention and has faster convergence speed towards the concavity and bigger time step.

Published
2007
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