Ensemble of convolutional neural networks to improve animal audio classification

Abstract In this work, we present an ensemble for automated audio classification that fuses different types of features extracted from audio files. These features are evaluated, compared, and fused with the goal of producing better classification accuracy than other state-of-the-art approaches witho...

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Bibliografiska uppgifter
Huvudupphovsmän: Loris Nanni, Yandre M. G. Costa, Rafael L. Aguiar, Rafael B. Mangolin, Sheryl Brahnam, Carlos N. Silla
Materialtyp: Artigo
Språk:Inglês
Publicerad: SpringerOpen 2020-05-01
Serie:EURASIP Journal on Audio, Speech, and Music Processing
Ämnen:
Audio classification
Texture
Deep learning
Handcrafted features
Ensemble of classifiers
Pattern recognition
Länkar:http://link.springer.com/article/10.1186/s13636-020-00175-3
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