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Recently, advanced multimedia technologies enable a rapid growth of music data. It is accordingly a challenging issue to effectively retrieve the desired music pieces from a music collection. Traditional solutions for music retrieval can be divided into two types, namely text-based music retrieval and content-based music retrieval. However, it is difficult to satisfy both textual-percept and audio-content...
Nowadays, content-based image retrieval (CBIR) is the mainstay of image retrieval systems. To be more profitable, relevance feedback techniques were incorporated into CBIR such that more precise results can be obtained by taking user's feedbacks into account. However, existing relevance feedback-based CBIR methods usually request a number of iterative feedbacks to produce refined search results, especially...
Up to the present, the contemporary studies are not really successful in image annotation due to some critical problems like diverse regularities between visual features and human concepts. Such diverse regularities make it hard to annotate the image semantics correctly. In this paper, we propose a novel approach called AICDM (Annotation by Image-Concept Distribution Model) for image annotation by...
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