Region Prediction from Hungarian Folk Music Using Convolutional Neural Networks
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-30490-4_47
Reference33 articles.
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3. Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: Synthetic Minority Over-sampling Technique. J. Artif. Intell. Res. 16, 321–357 (2002). https://doi.org/10.1613/jair.953
4. Choi, K., Fazekas, G., Sandler, M., Cho, K.: Convolutional recurrent neural networks for music classification. In: Proceedings of the International Conference on Acoustics, Speech and Signal Processing, New Orleans, LA, USA, pp. 2392–2396. IEEE (2017). https://doi.org/10.1109/icassp.2017.7952585
5. Cornelis, O., Lesaffre, M., Moelants, D., Leman, M.: Access to ethnic music: advances and perspectives in content-based music information retrieval. Signal Process. 90(4), 1008–1031 (2010). https://doi.org/10.1016/j.sigpro.2009.06.020
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