C-S 101- Intro to Computing Fall 2006 http://charity.cs.uwlax.edu Format Large lectures once per week Dr. Kenny Hunt (First Half) / Dr. Zheng? (Second Half) hunt.kenn@uwlax.edu Small lectures three times per week Mark Headington / Keith Burand / Steve Inglett Details

ByUncalibrated reconstruction. Calibration with a rig Uncalibrated epipolar geometry Ambiguities in image formation Stratified reconstruction Autocalibration with partial scene knowledge. Uncalibrated Camera. calibrated coordinates. Linear transformation. pixel coordinates.

ByAdaboost. Derek Hoiem March 31, 2004. Outline. Background Adaboost Algorithm Theory/Interpretations Practical Issues Face detection experiments. What’s So Good About Adaboost. Improves classification accuracy Can be used with many different classifiers Commonly used in many areas

ByWavelet & Neurowavelet. Provided by: Seyed Ehsan Safavieh. What is wavelet?. Wavelet transforms a signal into components of different frequencies, allowing to study each component separately.

ByAdaboost. Derek Hoiem March 31, 2004. Outline. Background Adaboost Algorithm Theory/Interpretations Practical Issues Face detection experiments. What’s So Good About Adaboost. Improves classification accuracy Can be used with many different classifiers Commonly used in many areas

ByParallel Methods for Nano/Materials Science Applications. (Electronic Structure Calculations). Andrew Canning Computational Research Division LBNL & UC Davis, Applied Science Dept. Outline. Introduction to Nano/Materials science Electronic Structure Calculations (DFT)

ByUsing Excel Solver for Linear Optimization Problems. Wendy Pitchko Irene Meglis Shawn Lemko. What is Solver?. Solver is an Add-In for Microsoft Excel which can solve optimization problems, including multiple constraint problems. You can maximize, minimize, or set a target value to achieve.

ByMid-term Review Chapters 2-7. Review Agents (2.1-2.3) Review State Space Search Problem Formulation (3.1, 3.3) Blind (Uninformed) Search (3.4) Heuristic Search (3.5) Local Search (4.1, 4.2) Review Adversarial (Game) Search (5.1-5.4) Review Constraint Satisfaction (6.1-6.4)

ByAnnouncements. Take home quiz given out Thursday 10/23 Due 10/30. Matching Sets of Point Features. Find best transformation. Similarity transformation, thin-plate splines. Measure how good it is.

ByON LIBRATION POINT ORBITS . H/P 2009/04/29-13:24:24UT. OPS-G FORUM Martin Hechler, GFA ESOC 2009/4/3. 56 slides. Contents. Lagrange points in Sun-Earth system and orbits around them ESA missions at L 2 and L 1 (Sun-Earth): Why there ? In which orbits ?

ByPhotometric Image Formation. CSE 559: Computer Vision Guest Lecturer: Austin Abrams. Images / Demo from Steve Seitz, Wikipedia. How are images made?. One half: geometric vision “how the pixel projected onto the image” Today: photometric vision (aka radiometric)

ByArtificial Intelligent. Chapter 5 Blind / Un-informed Search. Uninformed search strategies. Uninformed search strategies use only the information available in the problem definition Breadth-first search Uniform-cost search Depth-first search Depth-limited search

ByCooperative protocols for wireless vehicular communication. Fatma Hrizi, Jerome Haerri and Christian Bonnet EURECOM, Mobile communication s department. Vehicular networks: The Challenges. Applications Safety Efficiency Entertainment, Internet access Key concept

ByADVANCED COMPUTATIONAL MODELS AND ALGORITHMS. Instructor: Dr. Gautam Das March 10, 2009 Class notes by Alexandra Stefan. Topics covered . Linear Programming (LP) Problem instance: Set of n real variables Set of restrictions in the form of linear inequalities

ByRecall: Pendulum. Unstable Pendulum. Exponential growth dominates. Equilibrium is unstable. Recall: Finding eigvals and eigvecs. Nonlinear systems: the qualitative theory Day 8: Mon Sep 20. Systems of 1st-order, linear, homogeneous equations. How we solve it (the basic idea).

ByOptimization in Excel. By Heng Zhang. Linear Programming: A Simple Model. (Objective Function) (Constraint 1) ( Constraint 2) (Non-Negativity Constraint). Example Revisited. (Objective Function) (Constraint 1) ( Constraint 2)

ByBioinformatics Applications and Feature Selection for SVMs S. Mukherjee. Outline. I. Basic Molecular biology II. Some Bioinformatics problems III. Microarray technology a. Purpose b. cDNA and Oligonucleotide arrays c. Yeast experiment IV. Cancer classification using SVMs

ByBelos: A Framework for Next-generation Iterative Linear Solvers April 7 th , 2008 Mike Heroux Rich Lehoucq Mike Parks Heidi Thornquist (Lead).

ByIntroduction To Non–linear Optimization Department of Mechanical Engineering Universiti Tenaga Nasional. PART I. Optimization Tree. Figure 1: Optimization tree. What is Optimization?. Optimization is an iterative process by which a desired solution

ByIntroduction To Non–linear Optimization. PART I. Optimization Tree. Figure 1: Optimization tree. What is Optimization?. Optimization is an iterative process by which a desired solution (max/min) of the problem can be found while satisfying all its constraint or bounded conditions.

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