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In Multiple Classifier Systems, Vol. 2096 (2001), pp. 378-387, doi:10.1007/3-540-48219-9_38 Key: citeulike:11979764
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In this paper we discuss classifier architectures to categorize time series. Three different architectures for the fusion of local classifier decisions are presented and applied to classify recordings of cricket songs. Different features from local time windows are extracted automatically from the waveform of the sound patterns. These features are used to classify the whole time series. We present results for all three classifier architectures on a data set of 28 different categories.
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