'Nearest neighbour' diaporamas de présentation

Automatic Image Stitching using Invariant Features

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L2 and L1 Criteria for K-Means Bilinear Clustering

L2 and L1 Criteria for K-Means Bilinear Clustering. B. Mirkin School of Computer Science Birkbeck College, University of London

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FIL SPM Course May 2011 Spatial preprocessing

FIL SPM Course May 2011 Spatial preprocessing. Ged Ridgway With thanks to John Ashburner a nd the FIL Methods Group. fMRI time-series m ovie. Preprocessing overview. REALIGN. COREG. SEGMENT. NORM WRITE. SMOOTH. ANALYSIS. Preprocessing overview. Input. fMRI time-series.

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Chapter 12: Cluster analysis and segmentation of customers

Chapter 12: Cluster analysis and segmentation of customers . Commercial applications. A chain of radio-stores uses cluster analysis for identifying three different customer types with varying needs.

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Approximate genealogical inference

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CHAPTER 2 : Linear codes

CHAPTER 2 : Linear codes. ABSTRACT Most of the important codes are special types of so-called linear codes. Linear codes are of very large importance because they have very concise description, very nice properties, very easy encoding And ,

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Introduction to Hadronic Final State Reconstruction in Collider Experiments (Part VII & VIII)

Introduction to Hadronic Final State Reconstruction in Collider Experiments (Part VII & VIII). Peter Loch University of Arizona Tucson, Arizona USA. Validity of Jet Algorithms. Need to be valid to any order of perturbative calculations

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Rugby players, Ballet dancers, and the Nearest Neighbour Classifier

COMP24111 lecture 2. Rugby players, Ballet dancers, and the Nearest Neighbour Classifier. A Problem to Solve with Machine Learning. Distinguish rugby players from ballet dancers. You are provided with a few examples. Fallowfield rugby club (16). Rusholme ballet troupe (10). Task

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Instance Based Learning

Instance Based Learning. Ata Kaban The University of Birmingham. Today we learn: K-Nearest Neighbours Locally weighted regression Case-based reasoning Lazy and eager learning. Instance-based learning. One way of solving tasks of approximating discrete or real valued target functions

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SMOS Validation Rehearsal Campaign Mediterranean flights

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Productivity

Productivity. (a)1.65 t/ha (b)490 mm (c)too much water rots the plant inadequate aeration nutrient deficiency toxic concentration of some element. strong / high positive correlation

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Nearest Neighbour Condensing and Editing

Nearest Neighbour Condensing and Editing. David Claus February 27, 2004 Computer Vision Reading Group Oxford. Nearest Neighbour Rule. Non-parametric pattern classification. Consider a two class problem where each sample consists of two measurements ( x,y ).

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Interpolation of real-time ozone measurements in Europe

Interpolation of real-time ozone measurements in Europe. Results of a feasibility exercise for the Neighbourhood project Bill Oates bill.oates@atkinsglobal.com. Objectives. Review of available interpolation method and operational constraints Tests on archive data Tests on real-time data.

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Similarity-based Classifier Combination for Decision Making

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Image Interpolator

Image Interpolator. Supervisor By : Dr. Rajeev Srivastava Prashant Bhutani Associate Professor CSE, IIT-BHU . Abstract. Image interpolation is the process of resizing or remapping an image.

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Preferential top-k search over local data

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Spatial models for plant breeding trials

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Outlier Detection Using k-Nearest Neighbour Graph

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More on Microarrays

More on Microarrays. Chitta Baral Arizona State University. Some case studies. Yeast cell cycle Goal: Find groups of yeast genes whose expression profiles are similar over a 24-hour period.

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Nearest Neighbour Index

Nearest Neighbour Index. Geography Settlement. What is it?. X. X. X. X. X. X. X. X. X. X. X. X. X. X. X. X. X. Rn=2.15. Rn=0.0. Rn=1.0. X. X. X. X. X. Linear Clustering (nucleated) random regluar-uniform

274 views • 9 slides