2 results match your criteria: "Grenoble Institute of Technology and Centre National de la Recherche Scientifique[Affiliation]"

Many marine mammals produce highly nonlinear frequency modulations. Determining the time-frequency support of these sounds offers various applications, which include recognition, localization, and density estimation. This study introduces a low parameterized automated spectrogram segmentation method that is based on a theoretical probabilistic framework.

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This paper analyzes an 8-month time series (November 2005 to June 2006) of underwater noise recorded at the mouth of the Amundsen Gulf in the marginal ice zone of the western Canadian Arctic when the area was >90% ice covered. The time-series of the ambient noise component was computed using an algorithm that filtered out transient acoustic events from 7-min hourly recordings of total ocean noise over a [0-4.1] kHz frequency band.

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