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ECCV
2000
Springer
16 years 8 months ago
A Probabilistic Background Model for Tracking
A new probabilistic background model based on a Hidden Markov Model is presented. The hidden states of the model enable discrimination between foreground, background and shadow. Th...
Jens Rittscher, Jien Kato, Sébastien Joga, ...
ICIP
2006
IEEE
16 years 8 months ago
Developing an Efficient Region Growing Engine for Image Segmentation
Image segmentation is a crucial part of image processing applications. Currently available approaches require significant computer power to handle large images. We present an effi...
Emanuel Gofman
CCGRID
2007
IEEE
16 years 1 months ago
Profiling Computation Jobs in Grid Systems
The existence of good probabilistic models for the job arrival process and job characteristics is important for the improved understanding of grid systems and the prediction of th...
Michael Oikonomakos, Kostas Christodoulopoulos, Em...
SEMCO
2007
IEEE
16 years 1 months ago
Learning by Reading by Learning to Read
Knowledge-based natural language processing systems learn by reading, i.e., they process texts to extract knowledge. The performance of these systems crucially depends on knowledg...
Sergei Nirenburg, Tim Oates, Jesse English
GECCO
2007
Springer
139views Optimization» more  GECCO 2007»
16 years 1 months ago
The role of speciation in spatial coevolutionary function approximation
The role of space is more and more accepted as a way to dramatically improve the success of coevolutionary function approximation. The process behind this success however is not y...
Folkert de Boer, Paulien Hogeweg