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Adaptive Multimedia Retrieval: Retrieval, User, and Semantics

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Cover of 'Adaptive Multimedia Retrieval: Retrieval, User, and Semantics'

Table of Contents

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    Book Overview
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    Chapter 1 Learning Distance Functions for Automatic Annotation of Images
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    Chapter 2 Ontology: Use and Abuse
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    Chapter 3 Imagination: Exploiting Link Analysis for Accurate Image Annotation
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    Chapter 4 Automatic Image Annotation Using a Visual Dictionary Based on Reliable Image Segmentation
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    Chapter 5 Improving Automatic Image Annotation Based on Word Co-occurrence
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    Chapter 6 Automatic Image Annotation with Relevance Feedback and Latent Semantic Analysis
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    Chapter 7 A Novel Retrieval Refinement and Interaction Pattern by Exploring Result Correlations for Image Retrieval
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    Chapter 8 User Modelling for Interactive User-Adaptive Collection Structuring
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    Chapter 9 Searching for Music Using Natural Language Queries and Relevance Feedback
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    Chapter 10 Automatically Detecting Members and Instrumentation of Music Bands Via Web Content Mining
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    Chapter 11 A System for Automatic Chord Transcription from Audio Using Genre-Specific Hidden Markov Models
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    Chapter 12 Information Fusion in Multimedia Information Retrieval
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    Chapter 13 Multi-level Fusion for Semantic Video Content Indexing and Retrieval
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    Chapter 14 Image Data Source Selection Using Gaussian Mixture Models
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    Chapter 15 Designing a Peer-to-Peer Architecture for Distributed Image Retrieval
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    Chapter 16 Comparison of Dimension Reduction Methods for Database-Adaptive 3D Model Retrieval
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    Chapter 17 Smart Photo Sticking
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    Chapter 18 How to Use SIFT Vectors to Analyze an Image with Database Templates
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    Chapter 19 Video Semantic Content Analysis Framework Based on Ontology Combined MPEG-7
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    Chapter 20 Trajectory Annotation and Retrieval Based on Semantics
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Title
Adaptive Multimedia Retrieval: Retrieval, User, and Semantics
Published by
Springer Berlin Heidelberg, June 2008
DOI 10.1007/978-3-540-79860-6
ISBNs
978-3-54-079859-0, 978-3-54-079860-6
Editors

Boujemaa, Nozha, Detyniecki, Marcin, Nürnberger, Andreas

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 22%
Student > Master 2 22%
Student > Ph. D. Student 1 11%
Student > Doctoral Student 1 11%
Professor > Associate Professor 1 11%
Other 1 11%
Unknown 1 11%
Readers by discipline Count As %
Computer Science 6 67%
Business, Management and Accounting 1 11%
Engineering 1 11%
Unknown 1 11%