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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

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    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
  5. Altmetric Badge
    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
  14. Altmetric Badge
    Chapter 13 Multi-level Fusion for Semantic Video Content Indexing and Retrieval
  15. Altmetric Badge
    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
  20. Altmetric Badge
    Chapter 19 Video Semantic Content Analysis Framework Based on Ontology Combined MPEG-7
  21. Altmetric Badge
    Chapter 20 Trajectory Annotation and Retrieval Based on Semantics
Attention for Chapter 13: Multi-level Fusion for Semantic Video Content Indexing and Retrieval
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Chapter title
Multi-level Fusion for Semantic Video Content Indexing and Retrieval
Chapter number 13
Book title
Adaptive Multimedia Retrieval: Retrieval, User, and Semantics
Published in
Lecture notes in computer science, July 2007
DOI 10.1007/978-3-540-79860-6_13
Book ISBNs
978-3-54-079859-0, 978-3-54-079860-6
Authors

Benoit Huet, Rachid Benmokhtar, Benmokhtar, Rachid, Huet, Benoit

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 25%
Professor > Associate Professor 2 25%
Student > Master 1 13%
Professor 1 13%
Researcher 1 13%
Other 1 13%
Readers by discipline Count As %
Computer Science 4 50%
Mathematics 1 13%
Psychology 1 13%
Engineering 1 13%
Unknown 1 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 October 2012.
All research outputs
#20,169,675
of 22,681,577 outputs
Outputs from Lecture notes in computer science
#6,982
of 8,122 outputs
Outputs of similar age
#65,988
of 68,367 outputs
Outputs of similar age from Lecture notes in computer science
#13
of 15 outputs
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We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.