33 citations · 34 across the 3 of their papers we have counts for
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cs.SD2019
Random Projections of Mel-Spectrograms as Low-Level Features for Automatic Music Genre Classification
Juliano Henrique Foleiss, Tiago Fernandes Tavares
In this work, we analyse the random projections of Mel-spectrograms as low-level features for music genre classification. This approach was compared to handcrafted features, featur…
cs.SD2019★ 33 cited
Texture Selection for Automatic Music Genre Classification
Juliano H. Foleiss, Tiago F. Tavares
Music Genre Classification is the problem of associating genre-related labels to digitized music tracks. It has applications in the organization of commercial and personal music co…