'Conditional probability density' diaporamas de présentation

Bayesian Decision Theory (Sections 2.1-2.2)

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Probability

Probability. a tutorial on Bayesian , Conditional prob. Gaussian , likelihood, etc. KH W ong. Introduction. Bayesian rule Conditional probability density Prior and Posterior probability densities Gaussian Maximum likelihood. Bayesian rules. Bayesian rules. P(B|A)=P(A|B)P(B)/P(A )

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Mega-boundaries

Mega-boundaries. Temporal video boundary detection. Mega-boundaries. Mega boundaries are defined between macro segments that exhibit different structural and feature consistency. A good example of mega boundaries application is commercial detection. Commercial detection.

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Statistics 270 - Lecture 19

Statistics 270 - Lecture 19. Continue Chapter 5 today. Definition. The marginal probability density function for continuous random variables X and Y, denoted by f X (x) and f Y (y) , respectively, are given by. Example:.

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