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IDA
2005
Springer
15 years 5 months ago
Biological Cluster Validity Indices Based on the Gene Ontology
With the invention of biotechnological high throughput methods like DNA microarrays and the analysis of the resulting huge amounts of biological data, clustering algorithms gain ne...
Nora Speer, Christian Spieth, Andreas Zell
WABI
2005
Springer
179views Bioinformatics» more  WABI 2005»
15 years 5 months ago
Spectral Clustering Gene Ontology Terms to Group Genes by Function
Abstract. With the invention of biotechnological high throughput methods like DNA microarrays, biologists are capable of producing huge amounts of data. During the analysis of such...
Nora Speer, Christian Spieth, Andreas Zell
FQAS
2004
Springer
126views Database» more  FQAS 2004»
15 years 5 months ago
Cluster Characterization through a Representativity Measure
Clustering is an unsupervised learning task which provides a decomposition of a dataset into subgroups that summarize the initial base and give information about its structure. We ...
Marie-Jeanne Lesot, Bernadette Bouchon-Meunier
CVPR
2005
IEEE
16 years 1 months ago
Shock Filters Based on Implicit Cluster Separation
One of the classic problems in low level vision is image restoration. An important contribution toward this effort has been the development of shock filters by Osher and Rudin [1]...
Vinay P. Namboodiri, Subhasis Chaudhuri
ICDCS
2009
IEEE
15 years 9 months ago
CLIQUE: Role-Free Clustering with Q-Learning for Wireless Sensor Networks
Clustering and aggregation inherently increase wireless sensor network (WSN) lifetime by collecting information within a cluster at a cluster head, reducing the amount of data thr...
Anna Förster, Amy L. Murphy