1. Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: Advances in neural information processing systems, pp. 1097–1105. (2012)
2. Gemmeke, J.F., Ellis, P.D., Freedman, D., Jansen, A., Lawrence, W., Moore, C.R., Ritter, M.: Audio set: An ontology and human-labeled dataset for audio events. In: 2017 IEEE international conference on acoustics, speech and signal processing (ICASSP), p. 5. IEEE, New Orleans, LA, USA
3. Hershey, S., Chaudhuri, S., Ellis, D.P., Gemmeke, J.F., Jansen, A., Moore, R.C., Plakal, M., Platt, D., Saurous, R.A., Seybold, B., Slaney, M.: CNN architectures for large-scale audio classification. Weiss, Kevin Wilson Google, Inc., New York, NY, and Mountain View, CA, USA
4. Moss, J.C., Hammond, J.K.: A comparison between the modified spectrogram and the pseudo-Wigner-Ville distribution with and without modification
5. Scikit-learn.: Multiclass and multilabel algorithms. Retrieved from Scikit-learn Documentation: https://scikit-learn.org/stable/modules/multiclass.html