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- W1998131433 abstract "Two types of artificial neural networks are used to determine a sufficient subset of data for reasonable classification of musical instrument based on performance data from motion capture. Feedforward and recurrent networks are trained on subsets of joint angles and centre of mass from performances by violists and clarinettists. A successfully learned mapping from the reduced set of input data to the correct instrument classification implies that the data subset carries sufficient information to identify an instrument. After training, cross-validation is performed by testing networks on previously unseen data. Finally, performance is compared with that of humans performing similar classification tasks based on the same data." @default.
- W1998131433 created "2016-06-24" @default.
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- W1998131433 date "2014-06-16" @default.
- W1998131433 modified "2023-09-23" @default.
- W1998131433 title "Brahms, Bodies and Backpropagation" @default.
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- W1998131433 doi "https://doi.org/10.1145/2617995.2618011" @default.
- W1998131433 hasPublicationYear "2014" @default.
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