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Content-based queries in multimedia sequence databases where information is sequential is a tough issue, especially when dealing with large-scale applications. One of the key points is similarity estimation between a query sequence and elements of the database. In this paper, we investigate two ways to compare multimedia sequences, one—that comes from the literature—being computed in the feature space while the other one is computed in a model space, leading to a representation less sensitive to noise. We compare these approaches by testing them on a real audio dataset, which points out the utility of working in the model space. 相似文献
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Swaileh Wassim Imbert Florent Soullard Yann Tavenard Romain Anquetil Eric 《International Journal on Document Analysis and Recognition》2023,26(3):289-302
International Journal on Document Analysis and Recognition (IJDAR) - Handwriting with digital pens is a common way to facilitate human–computer interaction through the use of online... 相似文献
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