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» Identifying Objects Using Cluster and Concept Analysis
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IEEEVAST
2010
14 years 6 months ago
Finding and visualizing relevant subspaces for clustering high-dimensional astronomical data using connected morphological opera
Data sets in astronomy are growing to enormous sizes. Modern astronomical surveys provide not only image data but also catalogues of millions of objects (stars, galaxies), each ob...
Bilkis J. Ferdosi, Hugo Buddelmeijer, Scott Trager...
ICIP
2008
IEEE
16 years 29 days ago
Using local regression kernels for statistical object detection
We present a novel approach to the problem of detection of visual similarity between a template image, and patches in a given image. The method is based on the computation of a lo...
Hae Jong Seo, Peyman Milanfar
BMCBI
2008
138views more  BMCBI 2008»
14 years 11 months ago
CASCADE: a novel quasi all paths-based network analysis algorithm for clustering biological interactions
Background: Quantitative characterization of the topological characteristics of protein-protein interaction (PPI) networks can enable the elucidation of biological functional modu...
Woochang Hwang, Young-Rae Cho, Aidong Zhang, Mural...
AUSDM
2006
Springer
124views Data Mining» more  AUSDM 2006»
15 years 3 months ago
Analyzing Harmonic Monitoring Data Using Data Mining
Harmonic monitoring has become an important tool for harmonic management in distribution systems. A comprehensive harmonic monitoring program has been designed and implemented on ...
Ali Asheibi, David Stirling, Danny Soetanto
HPDC
2010
IEEE
15 years 9 days ago
DiscFinder: a data-intensive scalable cluster finder for astrophysics
DiscFinder is a scalable approach for identifying large-scale astronomical structures, such as galaxy clusters, in massive observation and simulation astrophysics datasets. It is ...
Bin Fu, Kai Ren, Julio López, Eugene Fink, ...