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Unsupervised Clustering on Multi-Components Datasets: Applications on Images and Astrophysics Data

Description : This paper proposes an original approach to cluster multi-component data sets with an estimation of the number of clusters. From the construction of a minimal spanning tree with Prim's algorithm and the assumption that the vertices are approximately distributed according to a Poisson distribution, t...
Language(s) : English
Subject(s) : [INFO:INFO_TS] Computer Science/Signal and Image Processing , [SPI:SIGNAL] Engineering Sciences/Signal and Image processing , clustering , minimal spanning tree , divergence
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Contributor(s) :
Source(s) : Proceedings of the 16th European Signal Processing Conference, EUSIPCO-2008 , 16th European Signal Processing Conference (EUSIPCO-2008)
Publication Date(s) : 2008-08-25