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» An objective evaluation criterion for clustering
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ICDCN
2009
Springer
14 years 2 months ago
FTRepMI: Fault-Tolerant, Sequentially-Consistent Object Replication for Grid Applications
We introduce FTRepMI, a simple fault-tolerant protocol for providing sequential consistency amongst replicated objects in a grid, without using any centralized components. FTRepMI ...
Ana-Maria Oprescu, Thilo Kielmann, Wan Fokkink
MM
2006
ACM
221views Multimedia» more  MM 2006»
14 years 1 months ago
Video object segmentation by motion-based sequential feature clustering
Segmentation of video foreground objects from background has many important applications, such as human computer interaction, video compression, multimedia content editing and man...
Mei Han, Wei Xu, Yihong Gong
ICDAR
2003
IEEE
14 years 1 months ago
Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
Marisa E. Morita, Robert Sabourin, Flávio B...
ECCV
2002
Springer
14 years 9 months ago
Probabilistic Search for Object Segmentation and Recognition
Abstract. The problem of searching for a model-based scene interpretation is analyzed within a probabilistic framework. Object models are formulated as generative models for range ...
Ulrich Hillenbrand, Gerd Hirzinger
ICDE
1999
IEEE
139views Database» more  ICDE 1999»
14 years 9 months ago
Clustering Large Datasets in Arbitrary Metric Spaces
Clustering partitions a collection of objects into groups called clusters, such that similar objects fall into the same group. Similarity between objects is defined by a distance ...
Venkatesh Ganti, Raghu Ramakrishnan, Johannes Gehr...