'Central moments' presentation slideshows

Jonathan Corriveau Thesis Advisor: Dr. Shreekanth Mandayam

Three-dimensional shape characterization for particle aggregates using multiple projective representations. Jonathan Corriveau Thesis Advisor: Dr. Shreekanth Mandayam Committee: Dr. Beena Sukumaran and Dr. Robi Polikar. Rowan University College of Engineering 201 Mullica Hill Road

1.02k views • 82 slides

Structural information

Structural information. Structural information. Structural information deals with geometry of objects. We are able to deal with very limited amounts of structural information. How to interpret structural information ? We were showing b efore that this is difficult problem

662 views • 51 slides

Final Review

Final Review. Econ 240A. Outline. The Big Picture Processes to remember ( and habits to form) for your quantitative career (FYQC) Concepts to remember FYQC Discrete Distributions Continuous distributions Central Limit Theorem Regression. The Classical Statistical Trail. Rates &

489 views • 43 slides

OCR a survey

527 views • 37 slides

An Image Retrieval System with Automatic Query Modification

An Image Retrieval System with Automatic Query Modification. Source: IEEE Transactions on Multimedia 2002 Authors: Gaurav Aggarwal, Ashwin T. V. and Sugata Ghosal Speaker: Chih-Yang Lin. Problem. DB. Desired image. internet. Problem. Overhead in database search

254 views • 25 slides

Shape Recognition by Invariant Moments

282 views • 15 slides

Moment Generating Functions

Moment Generating Functions. Moment Generating Functions (I). Moment Generating Functions (II). M(t) is called the moment-generating function for Y , and cam be used to derive any non-central moments of the random variable (assuming it exists in a neighborhood around t =0).

421 views • 10 slides

Picture Comparison; now with shapes!

Picture Comparison; now with shapes!. Slightly weak during MS1, only colour comparison Several comparisons will be done Turn picture into greyscale to do shape comparison Use colour picture to do a colour histogram, and averaging/mixing. Histogram. Picture. Greyscale. Greyscale shapes.

194 views • 9 slides

Moments

Moments. Ku-Yaw Chang canseco@mail.dyu.edu.tw Assistant Professor, Department of Computer Science and Information Engineering Da-Yeh University. Moments of Random Variables. If x is a discrete random variable the expected value of x, denoted by E(x), is defined by

129 views • 9 slides