'Similar objects' diaporamas de présentation

Sensation and Perception

Sensation and Perception. The Biological Basis of Behavior: Unit III. II. Perception. Understanding and interpreting sensations from a stimulus. Don't read the words -just say the colors they're printed in, and do this aloud as fast as you can. III. Principles of Perception.

769 views • 60 slides

Totally Transformed

Totally Transformed. Using Cabri Jr. on the TI-83 or 84. The shape changes size and position The shape changes size but not position The shape changes position but not size . What happens In a rigid transformation. Rotation, Reduction, Reflection Translation, Reflection, Dilation

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Java Programming (Basic)

Java Programming (Basic). Review. Contents. Language Basics Classes and Objects Inheritance Polymorphism Interfaces Packages Exceptions Numbers and Strings I/O Conclusion. What is an Object?. Objects are key to understanding object-oriented technology.

482 views • 36 slides

Natural Language Processing Clustering

Natural Language Processing Clustering. July, 2002. Clustering. Partition a set of objects into groups or clusters . Similar objects are placed in the same group and dissimilar objects in different groups. Objects are described and clustered using a set of features and values.

256 views • 25 slides

Taxonomy

Taxonomy. Lecture 12. Topics. Tutorial Review Classification Frame Terminology Classical Taxonomy Using Classifications In system use In system development Review Preview. Tutorial Review-Dating System. Outer join to include unmatched persons as well as matched

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Geometry Wrap Up

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Learning Image Similarities via Probabilistic Feature Matching

Learning Image Similarities via Probabilistic Feature Matching. Ziming Zhang * , Ze-Nian Li, Mark Drew School of Computing Science, Simon Fraser University, Vancouver , B.C., Canada {zza27, li , mark}@ cs.sfu.ca. Outline. Introduction Probabilistic-matching based similarity learning

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Cluster Analysis

Cluster Analysis. Introduction. Also called classification analysis and numerical taxonomy Goal: assign objects to groups so that intra-group similarity and inter-group dissimilarity as maximized No (in)dependent variables Find naturally occurring groupings of objects.

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Phobias

Do you have any?. Phobias. What do you think caused them?. Behavioural Explanations. Watson & Raynor (1920) Study of classical conditioning. Aim. To see if a fear of a previously unfeared objects can be induced through classical conditioning

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Fun with Literary devices!

Fun with Literary devices!. Mr. macqueen. Alliteration:. The repetition of consonant sounds at the beginning of words. Peter Piper picked a peck of pickled peppers. The Wicked Witch of the West went her own way. allusion.

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Principles of Perception

Principles of Perception. Perceptual Inference. Definition: When we fill-in holes between our sensations to develop a perception. Perceptual Inference depends on experience Ex. Our brain helps cover movie goofs / continuity errors. Gestalt.

5.3k views • 14 slides

7.5 Other Objects in the Solar System

7.5 Other Objects in the Solar System. Comets, dwarf planets, meteoroids and asteroids are other important objects in the solar system Objects that circle the Sun beyond the orbit of Neptune are called trans- Neptunian objects

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Solar System Project: Saturn

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C.R.A.P.

C.R.A.P. Color The contrast and intensity of the text and background. Good color creates a page that is aesthetically pleasing and that people will want to visit. Repetition Repeating formatting effects through out a web page.

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Data analytics challenge

11 December 2013 CERN openlab IT Challenges workshop. Data analytics challenge. Thanks to all for the participation, constructive ideas , thanks to Manuel Martin Marquez for taking the notes. General.

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Who made glasses?

Who made glasses?. By name was here. Who made eyeglasses?. Roger Bacon, the forerunner of modern science, wrote of the magnification properties of lenses in 1268. His observations, based on experiments, were used by later scientists in the burgeoning studies of the natural sciences.

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CS790 Technical Writing for Computer Scientists Summer 2007

CS790 Technical Writing for Computer Scientists Summer 2007. How to Write Short Project Descriptions Sue Moon KAIST. Resume vs Curriculum Vitae. Resume One or two page summary of your skills, experience and education.

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Markov Logic and Deep Networks

Markov Logic and Deep Networks. Pedro Domingos Dept. of Computer Science & Eng. University of Washington. Weight of formula i. No. of true instances of formula i in x. Markov Logic Networks. Basic idea: Use first-order logic to compactly specify large non-i.i.d. models

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Repetition

Repetition. Repeating: Shapes & Design. Similar Objects.

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Similarity assessment for the analysis of 3D artefacts

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