PPT-Corrélation d'images numériques: Stratégies de régulari

Author : faustina-dinatale | Published Date : 2016-07-01

et enjeux didentification Stéphane Roux François Hild LMT ENSCachan Atelier  Problèmes Inverses  Nancy 7 Juin 2011 Relative displacement field Image 1 Image

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Corrélation d'images numériques: Stratégies de régulari: Transcript


et enjeux didentification Stéphane Roux François Hild LMT ENSCachan Atelier  Problèmes Inverses  Nancy 7 Juin 2011 Relative displacement field Image 1 Image 2 Image 1. Chapter 10. Outline . Section 10-1 Introduction. Section 10-2 Scatter Plots. Section 10-3 Correlation. Section 10-4 Regression. Section 10-5 Coefficient of Determination and Standard Error of the Estimate. Cum hoc ergo propter hoc:. . “With this, therefore because of this”. Correlation. A . relation existing between phenomena or things or between mathematical or statistical variables which tend to vary, be associated, or occur together in a way not expected on the basis of chance . Pb+Pb. collisions. Victor Roy. ITP Goethe . University Frankfurt. In collaboration with. L-G Pang, G-Y Qin, X-N Wang and G-L Ma. Plan of the talk. Motivation. Dynamical models . -3+1 D Ideal Hydro . ... beware. Definition. Var. (X+Y) = . Var. (X) + . Var. (Y) + 2·Cov(X,Y). The . correlation. between two random variables is a dimensionless number between 1 and -1.. Interpretation. Correlation measures the . Siwei. . Liu. 1,. Yang Zhou. 1. , Richard Palumbo. 2. , & Jane-Ling Wang. 1. 1. UC Davis; . 2. University of Rhode Island. Motivating Study. Physiological synchrony between romantic partners during nonverbal conditions. Coefficient. &. Line of Best Fit. . We first need to make . sure the . calculator is . CL. ea. R. . of all . previous content. . We first need to make . sure the . calculator is . CL. ea. R. . They replace the value of an image pixel with a combination of its neighbors. Basic operations in images. Shift Invariant. Linear. Thanks to David Jacobs for the use of some slides. Consider 1D images. Linear Function. Y = a + bX. Fixed and Random Variables. A FIXED variable is one for which you have every possible value of interest in your sample.. Example: Subject sex, female or male.. A RANDOM variable is one where the sample values are randomly obtained from the population of values.. Pinyan Lu . Microsoft Research Asia. Joint with . Liang Li (Peking University) . Yitong Yin (Nanjing University). Spin Systems. System . and spin states . Configuration . Edge function . Vertex function b: [q]->. Once you know the correlation coefficient for your sample, you might want to determine whether this correlation occurred by chance.. Or does the relationship you found in your sample really exist in the population or were your results a fluke?. Objective. : To look for relationships between two quantitative variables. Scatterplots. Scatterplots. . may be the most common and most effective display for data. . In a scatterplot, you can see patterns, trends, relationships, and even the occasional extraordinary value sitting apart from the others.. Var. (X Y) = . Var. (X) . Var. (Y) 2·Cov(X,Y). The . correlation. between two random variables is a dimensionless number between 1 and -1.. Interpretation. Correlation measures the . strength. of the . a measure of the extent to which two variables change together.. How well does A predict B?. The correlation may be positive, negative, or have no relationship.. Correlation. A . positive correlation . Mary Forsythe, Graeme Kelly, Javier Garcia Pereda. IWW14, 24/04/2018. www.metoffice.gov.uk © Crown Copyright 2017, Met Office. © Crown copyright Met Office.

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