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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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Hlavní autoři: Loris Nanni, Yandre M. G. Costa, Rafael L. Aguiar, Rafael B. Mangolin, Sheryl Brahnam, Carlos N. Silla
Médium: Artigo
Jazyk:Inglês
Vydáno: SpringerOpen 2020-05-01
Edice:EURASIP Journal on Audio, Speech, and Music Processing
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On-line přístup:http://link.springer.com/article/10.1186/s13636-020-00175-3
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