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Furnariidae Species Classification Using Extreme Learning Machines and Spectral Information

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Advances in Artificial Intelligence - IBERAMIA 2018 (IBERAMIA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11238))

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Abstract

Automatic bird species classification and identification are issues that have aroused interest in recent years. The main goals involve more exhaustive environmental monitoring and natural resources managing. One of the more relevant characteristics of calling birds is the vocalisation because this allows to recognise species or identify new ones, to know its natural history and macro-systematic relations, among others. In this work, some spectral-based features and extreme learning machines (ELM) are used to perform bird species classification. The experiments were carried on using 25 species of the family Furnariidae that inhabit the Paranaense Littoral region of Argentina (South America) and were validated in a cross-validation scheme. The results show that ELM classifier obtains high classification rates, more than 90% in accuracy, and the proposed features overperform the baseline features.

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Notes

  1. 1.

    http://www.xeno-canto.org/.

  2. 2.

    http://ibc.lynxeds.com/.

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Acknowledgements

The authors wish to thank to Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT)(with PICT-2015-977), Universidad Nacional del Litoral (with CAID-PJ-50020150100055LI and CAID-PJ-50020150100059LI) and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), from Argentina, for their support.

Author information

Authors and Affiliations

  1. Instituto sınc(i), Universidad Nacional del Litoral - CONICET, Santa Fe, Argentina

    E. M. Albornoz, L. D. Vignolo & C. E. Martínez

  2. Instituto Nacional de Limnología, Universidad Nacional del Litoral - CONICET, Santa Fe, Argentina

    J. A. Sarquis

Authors
  1. E. M. Albornoz
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  2. L. D. Vignolo
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  3. J. A. Sarquis
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  4. C. E. Martínez
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Corresponding author

Correspondence to E. M. Albornoz .

Editor information

Editors and Affiliations

  1. Universidad Nacional del Sur, Bahía Blanca, Buenos Aires, Argentina

    Guillermo R. Simari

  2. University of Madeira, Funchal, Portugal

    Eduardo Fermé

  3. Universidad Nacional de Piura, Castilla-Piura, Peru

    Flabio Gutiérrez Segura

  4. Universidad Nacional de Trujillo, Trujillo, Peru

    José Antonio Rodríguez Melquiades

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Albornoz, E.M., Vignolo, L.D., Sarquis, J.A., Martínez, C.E. (2018). Furnariidae Species Classification Using Extreme Learning Machines and Spectral Information. In: Simari, G., Fermé, E., Gutiérrez Segura, F., Rodríguez Melquiades, J. (eds) Advances in Artificial Intelligence - IBERAMIA 2018. IBERAMIA 2018. Lecture Notes in Computer Science(), vol 11238. Springer, Cham. https://doi.org/10.1007/978-3-030-03928-8_14

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  • DOI: https://doi.org/10.1007/978-3-030-03928-8_14

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