RT Book, Section
T1 Network clustering by graph coloring: An application to astronomical images
A1 Zarrazola Rivera, Edwin
A1 Montero De Juan, Francisco Javier
A1 Yáñez Gestoso, Francisco Javier
A1 Gómez De Castro, Ana Inés
AB In this paper we propose an efficient and polynomial hierarchical clustering technique for unsupervised classification of items being connected by a graph. The output of this algorithm shows the cluster evolution in a divisive way, in such a way that s soon as two items are included in the same cluster they will join a common cluster until the last iteration, in which all the items belong to a singleton cluster. This output can be viewed as a fuzzy clustering in which for each alpha cut we have a standard cluster of the network. The clustering tool we present in this paper allows a hierarchical clustering of related items avoiding some unrealistic constraints that are quite often assumed in clustering problems. The proposed procedure is applied to a hierarchical segmentation problem in astronomical images.
PB IEEE
SN 978-1-4577-1676-8
YR 2011
FD 2011
LK https://hdl.handle.net/20.500.14352/45541
UL https://hdl.handle.net/20.500.14352/45541
LA eng
DS Docta Complutense
RD 9 abr 2025