Adaptive Multimedia Retrieval. Large-Scale Multimedia Retrieval and Evaluation: 9th International Workshop, AMR 2011, Barcelona, Spain, July 18-19, 20 by Marcin DetynieckiAdaptive Multimedia Retrieval. Large-Scale Multimedia Retrieval and Evaluation: 9th International Workshop, AMR 2011, Barcelona, Spain, July 18-19, 20 by Marcin Detyniecki

Adaptive Multimedia Retrieval. Large-Scale Multimedia Retrieval and Evaluation: 9th International…

byMarcin Detyniecki

Paperback | March 15, 2013

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This book constitutes the refereed post-proceedings of the 9th International Conference on Adaptive Multimedia Retrieval, AMR 2011, held in Barcelona, Spain, in July 2011. The 9 revised full papers and the invited contribution presented were carefully reviewed and selected from numerous submissions. The papers cover topics ranging from theoretical work to practical implementations and its evaluation, most of them dealing with audio or music media. They are organized in topical sections on evaluation and user studies, audio and music, image retrieval, and similarity and music.
Title:Adaptive Multimedia Retrieval. Large-Scale Multimedia Retrieval and Evaluation: 9th International…Format:PaperbackDimensions:141 pagesPublished:March 15, 2013Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3642374247

ISBN - 13:9783642374241

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Table of Contents

Learning-Based Interactive Retrieval in Large-Scale Multimedia.- A User Study of Visual Search Performance with Interactive 2D and 3D Storyboards.- An Illustrated Methodology for Evaluating ASR Systems.- Context-Aware Features for Singing Voice Detection in Polyphonic Music.- Personalization in Multimodal Music Retrieval.- Classifying Images at Scene Level: Comparing Global and Local Descriptors.- Effectiveness of ICF Features for Collection-Specific CBIR.- An Experimental Comparison of Similarity Adaptation Approaches.- Combining Sources of Description for Approximating Music Similarity Ratings.- An Approach to Automatic Music Band Member Detection Based on Supervised Learning.