'Local maxima' diaporamas de présentation

Object Recognition

Object Recognition. A wise robot sees as much as he ought, not as much as he can Search for objects that are important lamps outlets wall corners doors wall plugs. A mobile robot should be self-sufficient in power finding. In any case, we need information reduction. Segmentation - Review.

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Feature matching

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Recognition of 3D Objects or, 3D Recognition of Objects

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Comprehensive Survey of Extraction Techniques of Linear Features from Remote Sensing Imagery for Updating Road Spatial D

Ji Sang Park, PhD Candidate Dr. Raad A. Saleh, Scientist. Comprehensive Survey of Extraction Techniques of Linear Features from Remote Sensing Imagery for Updating Road Spatial Databases. Department of Civil and Environmental Engineering University of Wisconsin-Madison ERSC 12th Floor

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Image Segmentation

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Machine Learning and Review

Machine Learning and Review. Reading: C. 18. Bayesian Approach. Each observed training example can incrementally decrease or increase probability of hypothesis instead of eliminate an hypothesis Prior knowledge can be combined with observed data to determine hypothesis

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CS 4700: Foundations of Artificial Intelligence

CS 4700: Foundations of Artificial Intelligence. Bart Selman selman@cs.cornell.edu Local Search Readings R&N: Chapter 4:1 and 6:4. So far: methods that systematically explore the search space, possibly using principled pruning (e.g., A*)

657 views • 43 slides

Informed search algorithms

Informed search algorithms. Chapter 4. Material. Chapter 4 Section 1 - 3 Exclude memory-bounded heuristic search . Outline. Best-first search Greedy best-first search A * search Heuristics Local search algorithms Hill-climbing search Simulated annealing search Local beam search

785 views • 41 slides

Informed search algorithms

Informed search algorithms. Chapter 4. Material. Chapter 4 Section 1 - 3 Exclude memory-bounded heuristic search . Outline. Best-first search Greedy best-first search A * search Heuristics Local search algorithms Hill-climbing search Simulated annealing search Local beam search

680 views • 41 slides

The timing behaviour of radio pulsars

The timing behaviour of radio pulsars. George Hobbs Australia Telescope National Facility george.hobbs@csiro.au. Contents. Radio pulsars Pulsar timing A few things that you can do with pulsar timing Young pulsars - a new (predictive?) model for timing noise

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Allelic Pattern Sampler: Genetic Combinations Underlying Complex Diseases

Allelic Pattern Sampler: Genetic Combinations Underlying Complex Diseases. Polygenic diseases (traits). Polygenic diseases susceptibility arise due to contribution of a set of genes. Heterogeneity: different genetic backgrounds arise the same disease.

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Keypoint extraction: Corners

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Edge detection

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Ch 4. Heuristic Search

Ch 4. Heuristic Search. 4.0 Introduction( Heuristic ) 4.1 An Algorithm for Heuristic Search 4.1.1 Implementing Best-First Search 4.1.2 Implementing Heuristic Evaluation Functions 4.1.3 Heuristic Search and Expert Systems 4.3 Using Heuristics in Games 4.3.1 Minimax Procedure

855 views • 29 slides

A Gentle Introduction to the EM Algorithm

A Gentle Introduction to the EM Algorithm. Ted Pedersen Department of Computer Science University of Minnesota Duluth tpederse@d.umn.edu. A unifying methodology. Dempster, Laird & Rubin (1977) unified many strands of apparently unrelated work under the banner of The EM Algorithm

449 views • 24 slides

MultiModality Registration Using Hilbert-Schmidt Estimators

MultiModality Registration Using Hilbert-Schmidt Estimators. By: Srinivas Peddi Computer Integrated Surgery II April 6 th , 2001. Outline. Brief description of my project Things that have been successful so far and some results of that Key problems left to overcome

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An Introduction to MathCAD

An Introduction to MathCAD. Finding Solutions and Symbolic Maths. Finding Solutions. Finding roots of an equation Finding roots of a polynomial Solving systems of equations. Finding roots of an equation. Equations of the form f( x ) = 0 One equation in one unknown

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Canny Edge Detector

Canny Edge Detector. Smooth image with a Gaussian optimizes the trade-off between noise filtering and edge localization Compute the Gradient magnitude using approximations of partial derivatives 2x2 filters Thin edges by applying non-maxima suppression to the gradient magnitude

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Boundary Layer Meteorology Lecture 3

Boundary Layer Meteorology Lecture 3. Review summation (Einstein) notation Introduce some Non-Dimensional Numbers Reynolds averaging and Reynolds Stresses Review chapter 2 of Garratt. Summation (Einstein) notation. Some Non-Dimensional Numbers. Reynolds number: Re = VL/ ?

345 views • 7 slides