'Approximation error' presentation slideshows

Design of Curves and Surfaces by Multi Objective Optimization

Design of Curves and Surfaces by Multi Objective Optimization. Rony Goldenthal Michel Bercovier School of Computer Science and Engineering The Hebrew University of Jerusalem. Introduction. This work is about curves and surfaces :

886 views • 54 slides

A Hardware Processing Unit For Point Sets

A Hardware Processing Unit For Point Sets. S. Heinzle, G. Guennebaud, M. Botsch, M. Gross Graphics Hardware 2008. Motivation. Point-based graphics established Powerful algorithms Representation Processing Manipulation Rendering Decomposition Get neighborhood Operate on neighbors.

561 views • 44 slides

Surface Simplification Using Quadric Error Metrics

Surface Simplification Using Quadric Error Metrics. By Michael Garland and Paul S. Heckbert Carnegie Mellon University Presented by Lok Hwa and Taylor Holliday. Background / Related Work.

621 views • 38 slides

Extraction of Skeletal Meshes from Volumetric Data by Sparse Polynomial Approximation

Extraction of Skeletal Meshes from Volumetric Data by Sparse Polynomial Approximation. Yukie Nagai. Yutaka Ohtake. Kiwamu Kase. Hiromasa Suzuki. THE U NIVERSITY OF T OKYO RIKEN. Introduction Algorithm Details Result and Discussion.

381 views • 37 slides

Chapter 2 Errors in Numerical Methods and Their Impacts

Chapter 2 Errors in Numerical Methods and Their Impacts. Objectives. Know the difference between accuracy&precision Understand round-off error Understand approximation error and know how to apply. Content. Introduction Errors Round-off errors Approximate errror Total errors

305 views • 23 slides

Math 180

443 views • 18 slides

Chapter 3

Chapter 3. Approximations and Round-Off Errors Chapter 3. For many engineering problems, we cannot obtain analytical solutions.

270 views • 15 slides

Dual Energy

Dual Energy. Introduction. Reduce false alarms from EDS using dual energy techniques Use density and (effective) atomic number to identify harmful objects Limitations include : approximation error, boundary constraints, image artifacts, x-ray spectral drift. Overview of dual-energy.

310 views • 8 slides

Part (a)

73 views • 7 slides

WHY ARE DBNs SPARSE? Shaunak Chatterjee and Stuart Russell, UC Berkeley

WHY ARE DBNs SPARSE? Shaunak Chatterjee and Stuart Russell, UC Berkeley. Dynamic Bayesian Networks (DBNs) W hat are DBNs ?

105 views • 1 slides