Literature DB >> 20815432

Automatic identification of individual killer whales.

Judith C Brown1, Paris Smaragdis, Anna Nousek-McGregor.   

Abstract

Following the successful use of HMM and GMM models for classification of a set of 75 calls of northern resident killer whales into call types [Brown, J. C., and Smaragdis, P., J. Acoust. Soc. Am. 125, 221-224 (2009)], the use of these same methods has been explored for the identification of vocalizations from the same call type N2 of four individual killer whales. With an average of 20 vocalizations from each of the individuals the pairwise comparisons have an extremely high success rate of 80 to 100% and the identifications within the entire group yield around 78%.

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Year:  2010        PMID: 20815432     DOI: 10.1121/1.3462232

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  5 in total

Review 1.  Acoustic indexes for marine biodiversity trends and ecosystem health.

Authors:  Nadia Pieretti; Roberto Danovaro
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2020-11-02       Impact factor: 6.237

2.  Automatic detection, classification, and quantification of sciaenid fish calls in an estuarine soundscape in the Southeast United States.

Authors:  Agnieszka Monczak; Yiming Ji; Jamileh Soueidan; Eric W Montie
Journal:  PLoS One       Date:  2019-01-16       Impact factor: 3.240

3.  ORCA-SPOT: An Automatic Killer Whale Sound Detection Toolkit Using Deep Learning.

Authors:  Christian Bergler; Hendrik Schröter; Rachael Xi Cheng; Volker Barth; Michael Weber; Elmar Nöth; Heribert Hofer; Andreas Maier
Journal:  Sci Rep       Date:  2019-07-29       Impact factor: 4.379

4.  Deep Machine Learning Techniques for the Detection and Classification of Sperm Whale Bioacoustics.

Authors:  Peter C Bermant; Michael M Bronstein; Robert J Wood; Shane Gero; David F Gruber
Journal:  Sci Rep       Date:  2019-08-29       Impact factor: 4.379

5.  Bioacoustic Detection of Wolves: Identifying Subspecies and Individuals by Howls.

Authors:  Hanne Lyngholm Larsen; Cino Pertoldi; Niels Madsen; Ettore Randi; Astrid Vik Stronen; Holly Root-Gutteridge; Sussie Pagh
Journal:  Animals (Basel)       Date:  2022-03-02       Impact factor: 2.752

  5 in total

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