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» From Comparing Clusterings to Combining Clusterings
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ICML
2006
IEEE
14 years 8 months ago
Combined central and subspace clustering for computer vision applications
Central and subspace clustering methods are at the core of many segmentation problems in computer vision. However, both methods fail to give the correct segmentation in many pract...
Le Lu, René Vidal
ICANN
2009
Springer
14 years 10 days ago
A Two Stage Clustering Method Combining Self-Organizing Maps and Ant K-Means
This paper proposes a clustering method SOMAK, which is composed by Self-Organizing Maps (SOM) followed by the Ant K-means (AK) algorithm. The aim of this method is not to find an...
Jefferson R. Souza, Teresa Bernarda Ludermir, Lean...
DICTA
2003
13 years 9 months ago
Extracting Boundaries from Images by Comparing Cooccurrence Matrices
Abstract. This paper describes methods of extracting region boundaries from the frames of an image sequence by combining information from spatial or temporal cooccurrence matrices ...
Astrit Rexhepi, Azriel Rosenfeld
ICML
2005
IEEE
14 years 8 months ago
Comparing clusterings: an axiomatic view
This paper views clusterings as elements of a lattice. Distances between clusterings are analyzed in their relationship to the lattice. From this vantage point, we first give an a...
Marina Meila
AAAI
2010
13 years 9 months ago
Assisting Users with Clustering Tasks by Combining Metric Learning and Classification
Interactive clustering refers to situations in which a human labeler is willing to assist a learning algorithm in automatically clustering items. We present a related but somewhat...
Sumit Basu, Danyel Fisher, Steven M. Drucker, Hao ...