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Title: supervised learning of semantic classes for image annotation and retrieval
Page Link: supervised learning of semantic classes for image annotation and retrieval -
Posted By: chandujm
Created at: Wednesday 30th of June 2010 11:22:04 PM
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Title: Classes and Methods
Page Link: Classes and Methods -
Posted By: project uploader
Created at: Tuesday 21st of February 2012 03:42:38 PM
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Classes and Methods
Access Modifier
Public
Private
Protected
Internal
Public
The public keyword is an access modifier for types and type members.
Public access is the most permissive access level.
There are no restrictions on accessing public members.
Protected
The protected keyword is a member access modifier.
A protected member is accessible from within the class in which it is declared, and from within any class derived from the class that declared this member.
Internal
The internal ke ....etc

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Title: pdf file for miniproject examination result according to the classes
Page Link: pdf file for miniproject examination result according to the classes -
Posted By:
Created at: Monday 22nd of October 2012 11:39:54 PM
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Title: USING THE CONCEPTUAL COHESION OF CLASSES FOR FAULT PREDICTION IN OBJECT ORIENTED SYST
Page Link: USING THE CONCEPTUAL COHESION OF CLASSES FOR FAULT PREDICTION IN OBJECT ORIENTED SYST -
Posted By:
Created at: Thursday 08th of March 2012 02:12:09 PM
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Page Link: C classes - CS 638 Web Programming -
Posted By: computer girl
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Title: supervised learning of semantic classes for image anotation and retrieval
Page Link: supervised learning of semantic classes for image anotation and retrieval -
Posted By: chandujm
Created at: Monday 21st of June 2010 02:19:02 AM
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Abstract”A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as
classification problems where each class is defined as the group of database images labeled with a common semantic label. It is
shown that, by establishing this one-to-one correspondence between semantic labels and semantic classes, a minimum probability of
error annotation and retrieval are feasible with algorithms that are 1) conceptually simple, 2) computationally efficient, and 3) do not
require prior ....etc

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Title: USING THE CONCEPTUAL COHESION OF CLASSES FOR FAULT PREDICTION IN OBJECT ORIENTED SYST
Page Link: USING THE CONCEPTUAL COHESION OF CLASSES FOR FAULT PREDICTION IN OBJECT ORIENTED SYST -
Posted By: electronics seminars
Created at: Wednesday 13th of January 2010 09:52:37 AM
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USING THE CONCEPTUAL COHESION OF CLASSES FOR FAULT PREDICTION IN OBJECT ORIENTED SYSTEMS-SOFTWARE ENGINEERING

Abstract: High cohesion is desirable property in software systems to achieve reusability and maintainability. In this project we are measures for cohesion in Object-Oriented (OO) software reflect particular interpretations of cohesion and capture different aspects of it. In existing approaches the cohesion is calculate from the structural information for example method attributes and references. In conceptual cohesion of classes, i. ....etc

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Title: USING THE CONCEPTUAL COHESION OF CLASSES FOR FAULT PREDICTION IN OBJECT ORIENTED SYST
Page Link: USING THE CONCEPTUAL COHESION OF CLASSES FOR FAULT PREDICTION IN OBJECT ORIENTED SYST -
Posted By: computer science crazy
Created at: Friday 18th of September 2009 12:38:08 AM
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USING THE CONCEPTUAL COHESION OF CLASSES FOR FAULT PREDICTION IN OBJECT ORIENTED SYSTEMS

Abstract: High cohesion is desirable property in software systems to achieve reusability and maintainability. In this project we are measures for cohesion in Object-Oriented (OO) software reflect particular interpretations of cohesion and capture different aspects of it. In existing approaches the cohesion is calculate from the structural information for example method attributes and references. In conceptual cohesion of classes, i.e. in our project we a ....etc

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Title: PORTFOLIO MANAGEMENT OF ASSET CLASSES
Page Link: PORTFOLIO MANAGEMENT OF ASSET CLASSES -
Posted By: smart paper boy
Created at: Tuesday 02nd of August 2011 07:15:27 PM
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EXECUTIVE SUMMARY
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Title: Discriminative Learing and Recognition of Image set classes Using Canonical Correlati
Page Link: Discriminative Learing and Recognition of Image set classes Using Canonical Correlati -
Posted By: mechanical engineering crazy
Created at: Friday 28th of August 2009 04:32:15 AM
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Discriminative Learing and Recognition of Image set classes Using Canonical Correlation

Abstract:

Canonical angles or principle angle between the two dimensional sub-space.

Canonical angle is compared with the two main classical methods: parametric distribution based and non parametric sample based.

The classical linear discriminate analysis which we have to develop is to be maximizing the correlation with-in the class set and it has to minimize between the class-set.

Image set after transforming the discrimi ....etc

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