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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Detalles Bibliográficos
Main Authors: Loris Nanni, Yandre M. G. Costa, Rafael L. Aguiar, Rafael B. Mangolin, Sheryl Brahnam, Carlos N. Silla
Formato: Artigo
Idioma:Inglês
Publicado: SpringerOpen 2020-05-01
Series:EURASIP Journal on Audio, Speech, and Music Processing
Assuntos:
Audio classification
Texture
Deep learning
Handcrafted features
Ensemble of classifiers
Pattern recognition
Acceso en liña:http://link.springer.com/article/10.1186/s13636-020-00175-3
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