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- W1543802015 abstract "When classifying a sequence of objects, in an ordinary classification, where objects are assumed to be independently drawn from identical information sources, each object is classified independently. This assumption often causes deterioration in the accuracy of classification. In this paper, we consider a method to classify objects in a sequence by taking account of the context of the sequence. We define this problem as component classification and present a dynamic programming algorithm where a hidden Markov model is used to describe the probability distribution of the object sequences. We show the effectiveness of the component classification experimentally, using musical structure analysis.KeywordsHide Markov ModelSyntactical StructureDocument ImageComposite ObjectProbabilistic AutomatonThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
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- W1543802015 date "2002-01-01" @default.
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- W1543802015 title "Classification of Object Sequences Using Syntactical Structure" @default.
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- W1543802015 doi "https://doi.org/10.1007/3-540-45884-0_22" @default.
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