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- W2904703603 abstract "We apply computational-mathematical models to elucidate the brain's pattern recognition from music in tasks such as classification of music pieces according to style and historical period, such as Baroque, Classical and Romantic periods. We propose deep learning as the computational intelligence medium of choice to implement the model. The feasibility study reported below explores a special case to design an algorithm that could distinguish different styles of music, especially the Baroque music and the romantic music. The input is a piece of music, and the output will be the style of the music." @default.
- W2904703603 created "2018-12-22" @default.
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- W2904703603 date "2017-12-01" @default.
- W2904703603 modified "2023-09-23" @default.
- W2904703603 title "Deep Learning Empirical Topology for Classical Music Style Decision Making" @default.
- W2904703603 cites W2753897974 @default.
- W2904703603 doi "https://doi.org/10.1109/csci.2017.66" @default.
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