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» A Bayesian Computational Cognitive Model
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BMVC
2001
15 years 6 months ago
Classifying Surveillance Events from Attributes and Behaviour
In order to develop a high-level description of events unfolding in a typical surveillance scenario, each successfully tracked event must be classified into type and behaviour. I...
Paolo Remagnino, Graeme A. Jones
NAACL
2010
15 years 2 months ago
Learning Words and Their Meanings from Unsegmented Child-directed Speech
Most work on language acquisition treats word segmentation--the identification of linguistic segments from continuous speech-and word learning--the mapping of those segments to me...
Bevan K. Jones, Mark Johnson, Michael C. Frank
ICCV
2005
IEEE
16 years 6 months ago
Avoiding the "Streetlight Effect": Tracking by Exploring Likelihood Modes
Classic methods for Bayesian inference effectively constrain search to lie within regions of significant probability of the temporal prior. This is efficient with an accurate dyna...
David Demirdjian, Leonid Taycher, Gregory Shakhnar...
ICPR
2004
IEEE
16 years 5 months ago
Jet Based Feature Classification
In this paper, we investigate to which extent the "raw" mapping of Taylor series coefficients into jet-space can be used as a "language" for describing local i...
Kim Steenstrup Pedersen, Martin Lillholm
CVPR
2000
IEEE
16 years 6 months ago
Learning in Gibbsian Fields: How Accurate and How Fast Can It Be?
?Gibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronoun...
Song Chun Zhu, Xiuwen Liu