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Hierarchyless Simplification, Stripification and Compression of Triangulated Two-Manifolds

Hierarchyless Simplification, Stripification and Compression of Triangulated Two-Manifolds

Hierarchyless Simplification, Stripification and Compression of Triangulated Two-Manifolds Pablo Diaz-Gutierrez M. Gopi Renato Pajarola University of California, Irvine Introduction

By paul
(360 views)

Stochastic Approach for Link Structure Analysis (SALSA)

Stochastic Approach for Link Structure Analysis (SALSA)

Stochastic Approach for Link Structure Analysis (SALSA). Presented by Adam Simkins. SALSA. Created by Lempel Moran in 2000 Combination of HITS and PageRank. SALSA’s similarities to HITS and PageRank. SALSA uses authority and hub score

By Pat_Xavi
(240 views)

Lecture 13

Lecture 13

Lecture 13. CSE 331 Oct 2, 2009. Announcements. Please turn in your HW 3. Graded HW2, solutions to HW 3, HW 4 at the END of the class. Maybe extra lectures next week on proofs– check the blog!. Connected Component. Connected component (of s ) is the set of all nodes connected to s.

By afi
(168 views)

Lecture 15: Depth First Search

Lecture 15: Depth First Search

Lecture 15: Depth First Search. Shang-Hua Teng. A. A. B. B. D. F. F. E. E. D. C. C. Graphs. G= (V,E). Directed Graph (digraph) Degree: in/out. Undirected Graph Adjacency is symmetric. Graph Basics. The size of a graph is the number of its vertices

By irish
(242 views)

Euler Number Computation

Euler Number Computation

Euler Number Computation. By Kishore Kulkarni (Under the Guidance of Dr. Longin Jan Latecki). Outline. Connected Components & Holes Euler Number & its significance For Binary Images For Graphs Analogy between Euler number for graphs & binary images Concavities and Convexities

By Leo
(705 views)

CSE 554 Lecture 1: Binary Pictures

CSE 554 Lecture 1: Binary Pictures

CSE 554 Lecture 1: Binary Pictures. Fall 2016. Geometric Forms. Curves. Surfaces. Continuous forms Defined by mathematical functions E.g.: parabolas, splines, subdivision surfaces Discrete forms Disjoint elements with connectivity relations

By tao
(209 views)

What is a graph ?

What is a graph ?

What is a graph ?. 1. 2. 3. 5. 4. What is a graph ?. G=(V,E). V = a set of vertices E = a set of edges. edge = unordered pair of vertices. 1. 2. 3. 5. 4. What is a graph ?. G=(V,E). V = {1,2,3,4,5} E = {{1,5}, {3,5}, {2,3}, {2,4}, {3,4}}. 1. 2. 3. 5. 4. What is a graph ?.

By jenn
(117 views)

Image Feature Session 0 7

Image Feature Session 0 7

Course : COMP7116 - Computer Vision Effective Period : February 2018. Image Feature Session 0 7. Learning Objectives. After carefully listening this lecture, students will be able to do the following :

By albin
(399 views)

6.006- Introduction to Algorithms

6.006- Introduction to Algorithms

6.006- Introduction to Algorithms. Lecture 13 Prof. Constantinos Daskalakis CLRS 22.4-22.5. Graphs. G=(V,E) V a set of vertices Usually number denoted by n E Í VxV a set of edges (pairs of vertices) Usually number denoted by m Flavors:

By kin
(243 views)

Advanced Topics in Data Mining Special focus: Social Networks

Advanced Topics in Data Mining Special focus: Social Networks

Advanced Topics in Data Mining Special focus: Social Networks. Goal of the class. Address major trends in the analysis of social-network data Get you involved and interested Do something fun and cool. What is a social network?. Facebook LinkedIn ….

By aldis
(233 views)

Graph Traversals

Graph Traversals

Graph Traversals. Introduction Breadth-First Traversal. The Algorithm. Example. Implementation. Depth-First Traversals. Algorithms. Example. Implementation. Some traversal applications: Connected Components Strongly Connected Components Edge Classification Review Questions.

By ashlyn
(225 views)

I2.2 Large-Scale Information Network Processing Mid-Year Report

I2.2 Large-Scale Information Network Processing Mid-Year Report

I2.2 Large-Scale Information Network Processing Mid-Year Report. Charu Aggarwal (IBM) Christos Faloutsos (CMU) Ambuj Singh (UCSB) Xifeng Yan (UCSB). Task Setting. Indexing , Partitioning , and Distributed Processing on Time-Varying Networks. INARC I2.2 Mid-Year Report.

By gitel
(123 views)

CAP5415 Computer Vision Spring 2003

CAP5415 Computer Vision Spring 2003

CAP5415 Computer Vision Spring 2003. Khurram Hassan-Shafique. Detecting Edges in Image. Sobel Edge Detector. Edges. Threshold. Image I. Sobel Edge Detector. Sobel Edge Detector. Marr and Hildreth Edge Operator. Smooth by Gaussian Use Laplacian to find derivatives.

By valin
(15 views)

CS 585 Computational Photography

CS 585 Computational Photography

CS 585 Computational Photography. Nathan Jacobs. Administrivia. project 1: due Tuesday before midnight. Overview. point processing morphological operations more useful Matlab functions. Point Processing.

By nasia
(150 views)

Reconstructing Shredded Documents

Reconstructing Shredded Documents

Reconstructing Shredded Documents. Nathan Figueroa. Example: Original. Example: Shredded. Example: Reconstructed. Motivation. Method . Isolate: K-Means Segmentation. Pick K cluster means at random Assign each pixel to the nearest mean Compute a new mean for each cluster

By onofre
(166 views)

Systems Thinking Overview

Systems Thinking Overview

Systems Thinking Overview. TNT 2008 Sources from The Open University acknowledged. My Background. Fellow of Mech. Engg. & Management 40 years applying systems to business 13 years as independent consultant 25 years tutoring OU systems courses External examiner to Arab OU

By callie
(165 views)

An Out-of-core Algorithm for Isosurface Topology Simplification

An Out-of-core Algorithm for Isosurface Topology Simplification

An Out-of-core Algorithm for Isosurface Topology Simplification. Zo ë Wood Hughes Hoppe Mathieu Desbrun Peter Schröder. Problem. NEARLY INVISIBLE HANDLES. Discretely represented surface. Reconstruction as “isosurface” f ( x , y , z ) = 0. NOISY. Bad for simplification,

By herman
(100 views)

Moment-Based Global Registration of Echo Planar Diffusion-Weighted Images

Moment-Based Global Registration of Echo Planar Diffusion-Weighted Images

Moment-Based Global Registration of Echo Planar Diffusion-Weighted Images. 1. G. Kindlmann 1 , A.L. Alexander 2 , M. Lazar 2 , J. Lee 3 , T. Tasdizen 1 , R. Whitaker 1. 1 Scientific Computing and Imaging Institute, University of Utah

By molimo
(135 views)

Efficient Decomposed Learning for Structured Prediction

Efficient Decomposed Learning for Structured Prediction

Efficient Decomposed Learning for Structured Prediction. Rajhans Samdani Joint work with Dan Roth University of Illinois at Urbana-Champaign. Structured Prediction. Structured prediction : predicting a structured output variable y based on the input variable x

By bart
(115 views)

Problem: Semantic Segmentation

Problem: Semantic Segmentation

Scene Labeling Using Beam Search Under Mutex Constraints ID: O-2B-6 Anirban Roy and Sinisa Todorovic Oregon State University. Problem: Semantic Segmentation. Prior Work: Labeling Individual Superpixels. Random forest, Logistic regression

By arvin
(247 views)

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