A Novel Density-Based Clustering Framework by Using Level Set Method

In this paper, a new density-based clustering framework is proposed by adopting the assumption that the cluster centers in data space can be regarded as target objects in image space. First, the level set evolution is adopted to find an approximation of cluster centers by using a new initial boundar...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering Jg. 21; H. 11; S. 1515 - 1531
Hauptverfasser:	WANG, Xiao-Feng, HUANG, De-Shuang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.11.2009 IEEE Computer Society The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Applied sciences Artificial intelligence Boundaries Clustering Clustering algorithms Clustering methods Clusters Computer science; control theory; systems Computer systems and distributed systems. User interface Costs Data mining Data processing. List processing. Character string processing Density Density-based clustering Evolution Exact sciences and technology Image retrieval Image segmentation Information retrieval initial boundary Labeling Level set level set density level set method LSD Memory organisation. Data processing Pattern classification Pattern recognition. Digital image processing. Computational geometry Software Studies valley seeking clustering Valleys Cluster analysis Termination problem Contour line Data center initial boundary Outlier Image segmentation level set density valley seeking clustering Classification level set method Computer center Density-based clustering Point group
ISSN:	1041-4347, 1558-2191
Online-Zugang:	Volltext
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