Download Adaptive Multimedia Retrieval: Semantics, Context, and by Andreas Nürnberger, Sebastian Stober, Birger Larsen, Marcin PDF

By Andreas Nürnberger, Sebastian Stober, Birger Larsen, Marcin Detyniecki (eds.)

This e-book constitutes the completely refereed post-conference court cases of the tenth foreign convention on Adaptive Multimedia Retrieval, AMR 2012, held in Copenhagen, Denmark, in October 2012.

The 17 revised complete papers provided have been rigorously reviewed and chosen from various submissions. The papers disguise themes of state-of-the-art contributions, good points and class, situation context, language and semantics, tune retrieval, and adaption and HCI.

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Additional info for Adaptive Multimedia Retrieval: Semantics, Context, and Adaptation: 10th International Workshop, AMR 2012, Copenhagen, Denmark, October 24-25, 2012, Revised Selected Papers

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In: Proceedings of the ICME, pp. 1385–1388, July 2006 48. : A hierarchical approach to automatic musical genre classification. In: Proceedings of the DAFx, London, UK, Sept 2003 49. : Hierarchical automatic audio signal classification. J. Audio Eng. Soc. 52(7), 724–739 (2004) 50. : An adaptive system for music classification and tagging. In: International Workshop on Learning Semantics of Audio Signals (2009) 51. : Contentbased music information retrieval: current directions and future challenges.

In: Proceedings of the ISMIR (2004) 35. : Image features in music style recognition. In: Proceedings of the Central European Seminar on Computer Graphics (2012) 36. : A tensor-based approach for automatic music genre classification. In: Proceedings of the EUSIPCO, Lausanne, Switzerland (2008) 37. : Non-negative tensor factorization applied to music genre classification. IEEE Trans. Audio Speech Lang. Process. 18(8), 1955–1967 (2010) A Survey of Evaluation in Music Genre Recognition 43 38. : Aggregate features and Adaboost for music classification.

Relevance feedback in an adaptive space with one-class SVM for content-based music retrieval. In: Proceedings of the ICALIP, pp. 1153–1158, July 2008 62. : Improving music genre classification using collaborative tagging data. In: International Conference on Web Search and Data Mining, Barcelona, Spain, Feb 2009 63. : Content-based music genre classification using timbral feature vectors and support vector machine. In: Proceedings of the International Conference on Interaction Sciences, pp. 1095–1101, Nov 2009 64.

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