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EMMCVPR
2003
Springer
15 years 10 months ago
Watershed-Based Unsupervised Clustering
In this paper, a novel general purpose clustering algorithm is presented, based on the watershed algorithm. The proposed approach defines a density function on a suitable lattice,...
Manuele Bicego, Marco Cristani, Andrea Fusiello, V...
ICASSP
2010
IEEE
15 years 5 months ago
Evolutionary spectral clustering with adaptive forgetting factor
Many practical applications of clustering involve data collected over time. In these applications, evolutionary clustering can be applied to the data to track changes in clusters ...
Kevin S. Xu, Mark Kliger, Alfred O. Hero III
139
Voted
ICIP
2007
IEEE
16 years 6 months ago
Abnormal Event Detection from Surveillance Video by Dynamic Hierarchical Clustering
The clustering-based approach for detecting abnormalities in surveillance video requires the appropriate definition of similarity between events. The HMM-based similarity defined ...
Fan Jiang, Ying Wu, Aggelos K. Katsaggelos
ICPR
2008
IEEE
16 years 6 months ago
Active query selection for semi-supervised clustering
Semi-supervised clustering allows a user to specify available prior knowledge about the data to improve the clustering performance. A common way to express this information is in ...
Anil K. Jain, Pavan Kumar Mallapragada, Rong Jin
ICDM
2007
IEEE
140views Data Mining» more  ICDM 2007»
15 years 11 months ago
Finding Cohesive Clusters for Analyzing Knowledge Communities
Documents and authors can be clustered into “knowledge communities” based on the overlap in the papers they cite. We introduce a new clustering algorithm, Streemer, which fin...
Vasileios Kandylas, S. Phineas Upham, Lyle H. Unga...