'Scatter matrix' presentation slideshows

Dimensionality reduction

Dimensionality reduction. Usman Roshan CS 698 Fall 2013. Dimensionality reduction. What is dimensionality reduction? Compress high dimensional data into lower dimensions How do we achieve this?

541 views • 30 slides

Motion Analysis

Motion Analysis. Slides are from RPI Registration Class. Registration. Images are described as discrete sets of point locations associated with a geometric measurement Locations may have additional properties such as intensities and orientations Registration problem involves two parts:

482 views • 29 slides

Dimensionality reduction

Dimensionality reduction. Usman Roshan. Dimensionality reduction. What is dimensionality reduction? Compress high dimensional data into lower dimensions How do we achieve this?

471 views • 26 slides

Ch. 10: Linear Discriminant Analysis (LDA) based on slides from

Duncan Fyfe Gillies Carlos Thomaz authored the original version of these slides. Ch. 10: Linear Discriminant Analysis (LDA) based on slides from. Modified by Longin Jan Latecki Temple University latecki@temple.edu. The story so far:.

332 views • 26 slides

Face Recognition using PCA (Eigenfaces) and LDA (Fisherfaces)

Face Recognition using PCA (Eigenfaces) and LDA (Fisherfaces). Slides adapted from Pradeep Buddharaju. Principal Component Analysis. A N x N pixel image of a face, represented as a vector occupies a single point in N 2 -dimensional image space.

383 views • 20 slides

Face Recognition Rashmi Shastri

Face Recognition Rashmi Shastri. Problem definition. Determine the identity of a face in an image The image can be a frame from a video Processing needs to be fast Classification problem Need faces images for training. Motivation: Security. Recognize criminals

338 views • 16 slides

Hairong Qi, Gonzalez Family Professor Electrical Engineering and Computer Science

133 views • 12 slides

Regression Diagnostics

Regression Diagnostics. Regression Diagnostic asks 3 questions: Are the assumptions of multiple regression complied with? Is the model adequate? Is there anything unusual about any data points?. Checking for Non-violation of Assumptions.

272 views • 9 slides

Regression Diagnostics

Regression Diagnostics. Regression Diagnostic asks 3 questions: Are the assumptions of multiple regression complied with? Is the model adequate? Is there anything unusual about any data points?. Checking for Non-violation of Assumptions.

348 views • 9 slides

Lecture 21 Clustering (2)

252 views • 9 slides

Lecture 21 Clustering (2)

241 views • 9 slides

13. Component Analysis (also Chap 3)

Pattern Classification All materials in these slides were taken from Pattern Classification (2nd ed) by R. O. Duda, P. E. Hart and D. G. Stork, John Wiley & Sons, 2000 with the permission of the authors and the publisher. 13. Component Analysis (also Chap 3).

275 views • 5 slides

13. Component Analysis (also Chap 3)

Pattern Classification All materials in these slides were taken from Pattern Classification (2nd ed) by R. O. Duda, P. E. Hart and D. G. Stork, John Wiley & Sons, 2000 with the permission of the authors and the publisher. 13. Component Analysis (also Chap 3).

66 views • 5 slides