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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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please send me the ppt of the above mentioned topic ....etc

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Title: SEMINAR REPORT on Learning and Semantic Web
Page Link: SEMINAR REPORT on Learning and Semantic Web -
Posted By: Computer Science Clay
Created at: Sunday 14th of June 2009 03:48:52 AM
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Learning and Semantic Web
G. Santhosh Kumar
Dept. Of Computer Science
Cochin UniversityPage 2

What is Semantic Web?
?
Components of Semantic Web
?
Ontology
?
E-Learning @ Semantic Web
?
Advantages
?
Semantic Applications
AgendaPage 3

Size of the web
Size of the web
Y
The Indexed Web contains at least
45.33 billion pages
(Thursday, 07
February, 2008).
?
numbers of pages indexed by Google,
Windows Live Search (Msn Search),
Yahoo Search and Ask
?
Actual Size of the Web is higher than
this!Page 4

Types of Sear ....etc

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Title: Automatic Semantic Annotation of Real-World Web Images
Page Link: Automatic Semantic Annotation of Real-World Web Images -
Posted By: summer project pal
Created at: Saturday 29th of January 2011 10:33:21 PM
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Automatic Semantic Annotation of Real-World Web Images
A Seminar Report
by
Sarath S Nair
M105114
Department of Computer Science & Engineering
College of Engineering Trivandrum
Kerala - 695016
2010-11


Abstract
As the number of Web images is increasing at a rapid rate, searching them semantically
presents a significant challenge. Many raw images are constantly uploaded with few meaningful
direct annotations of semantic content, limiting their search and discovery. In this pap ....etc

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Title: ACTIVE LEARNING METHODS FOR INTERACTIVE IMAGE RETRIEVAL - IMAGE PROCESSING
Page Link: ACTIVE LEARNING METHODS FOR INTERACTIVE IMAGE RETRIEVAL - IMAGE PROCESSING -
Posted By: electronics seminars
Created at: Wednesday 13th of January 2010 10:02:00 AM
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ACTIVE LEARNING METHODS FOR INTERACTIVE IMAGE RETRIEVAL - IMAGE PROCESSING

Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensions are now being proposed to handle multimedia applications. This paper provides algorithms within a statistical framework to extend active learning for online content-based image retrieval (CBIR). The classification framework is presented with experiments to compare several powerful cla ....etc

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Title: COMMUNITIES AND EMERGING SEMANTICS IN SEMANTIC LINK NETWORK DISCOVERY AND LEARNING
Page Link: COMMUNITIES AND EMERGING SEMANTICS IN SEMANTIC LINK NETWORK DISCOVERY AND LEARNING -
Posted By: project topics
Created at: Wednesday 27th of April 2011 03:29:14 PM
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Abstract
The World Wide Web provides plentiful contents for Web-based learning, but its hyperlink-based architecture connects Web resources for browsing freely rather than for effective learning. To support effective learning, an e-learning system should be able to discover and make use of the semantic communities and the emerging semantic relations in a dynamic complex network of learning resources. Previous graph-based community discovery approaches are limited in ability to discover semantic communities. This paper first suggests the ....etc

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Title: matlab code for semi supervised margin analysis image retrieval
Page Link: matlab code for semi supervised margin analysis image retrieval -
Posted By:
Created at: Wednesday 03rd of July 2013 07:18:43 PM
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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: active learning methods for interactive image retrieval based on RETIN strategy
Page Link: active learning methods for interactive image retrieval based on RETIN strategy -
Posted By: teena abhilash
Created at: Sunday 25th of April 2010 10:04:53 PM
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What is the meaning of image utility in active learning methods for interactive image retrieval based on RETIN strategy? ....etc

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Title: A Novel Framework for Semantic Annotation and Personalized Retrieval of Sports Video
Page Link: A Novel Framework for Semantic Annotation and Personalized Retrieval of Sports Video -
Posted By: electronics seminars
Created at: Wednesday 13th of January 2010 10:05:47 AM
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abstract:
A Novel Framework for Semantic Annotation and Personalized Retrieval of Sports Video

Sports video annotation is important for sports video semantic analysis such as event detection and personalization. We propose a novel approach for sports video semantic annotation and personalized retrieval. Different from the state of the art sports video analysis methods which heavily rely on audio/visual features, the proposed approach incorporates web-casting text into sports video analysis.

Compared with previous approaches, the contri ....etc

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Title: active learning methods for interactive image retrieval image processing
Page Link: active learning methods for interactive image retrieval image processing -
Posted By: srinivasmahi
Created at: Monday 13th of December 2010 03:03:15 PM
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request:sir please send me full information about this project and ppt if possible what are the active methods for interactive image retrieval

my project abstract:
title:active learning methods for interactive image retrieval

RGB BASED IMAGE SEARCH ENGINE


Abstract:

Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, ....etc

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