Serial combination of multiple classifiers for automatic blue whale calls recognition

  • Authors:
  • Mohammed Bahoura;Yvan Simard

  • Affiliations:
  • Department of Engineering, Université du Québec í Rimouski, 300, allée des Ursulines, Rimouski, Qc, Canada G5L 3A1;Marine Sciences Institute, Université du Québec í Rimouski, 310, allée des Ursulines, Rimouski, Qc, Canada G5L 3A1 and Maurice Lamontagne Institute, Fisheries and Oceans Canada ...

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

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Abstract

In this paper, we propose a serial combination architecture of classifiers for automatic blue whale calls recognition. Based on class's best selection operator, the proposed system uses a best classifier for D call class followed by another one that efficiently discriminate the A and B calls. The first classifier uses the short-time Fourier transform to characterize the patterns, while the second uses the chirplet transform. Both classifiers are based on multi-layer perceptron neural network. The classification performance (95.55%) of the proposed system outperforms all tested single classifiers. The other advantages of the system are no requirement for adjusting a series of parameters and simple feature extraction.