• DocumentCode
    718479
  • Title

    Right whale detection using artificial neural network and principal component analysis

  • Author

    Pylypenko, Kostiantyn

  • Author_Institution
    Dept. of Acoust. & Acoustoelectronics, Nat. Tech. Univ. of Ukraine “KPI”, Kiev, Ukraine
  • fYear
    2015
  • fDate
    21-24 April 2015
  • Firstpage
    370
  • Lastpage
    373
  • Abstract
    In this paper applying PCA algorithm in order to preprocess data in North whale detection problem was proposed. It is shown that reducing number of features obtained from a spectrogram can prevent overfitting and increase performance of the classifier. Proposed classifier was based on a tree layer Neural Network with 50, 100 and 400 input neurons. Proposed technique achieved an F1 score of 90%.
  • Keywords
    neural nets; principal component analysis; signal classification; signal detection; trees (mathematics); zoology; PCA algorithm; artificial neural network; classifier; north whale detection problem; principal component analysis; right whale detection; spectrogram; tree layer neural network; Acoustics; Artificial neural networks; Conferences; Image reconstruction; Principal component analysis; Spectrogram; Whales; Artificial Neural Network; Principal Component Analysis; spectrogram; whale detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics and Nanotechnology (ELNANO), 2015 IEEE 35th International Conference on
  • Conference_Location
    Kiev
  • Type

    conf

  • DOI
    10.1109/ELNANO.2015.7146912
  • Filename
    7146912
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=718479