Zobrazeno 1 - 10
of 160
pro vyhledávání: '"Roch, Marie A"'
Autor:
Schäfer-Zimmermann, Julian C., Demartsev, Vlad, Averly, Baptiste, Dhanjal-Adams, Kiran, Duteil, Mathieu, Gall, Gabriella, Faiß, Marius, Johnson-Ulrich, Lily, Stowell, Dan, Manser, Marta B., Roch, Marie A., Strandburg-Peshkin, Ariana
Bioacoustic research, vital for understanding animal behavior, conservation, and ecology, faces a monumental challenge: analyzing vast datasets where animal vocalizations are rare. While deep learning techniques are becoming standard, adapting them t
Externí odkaz:
http://arxiv.org/abs/2406.01253
Autor:
Li, Pu, Roch, Marie, Klinck, Holger, Fleishman, Erica, Gillespie, Douglas, Nosal, Eva-Marie, Shiu, Yu, Liu, Xiaobai
Whistle contour extraction aims to derive animal whistles from time-frequency spectrograms as polylines. For toothed whales, whistle extraction results can serve as the basis for analyzing animal abundance, species identity, and social activities. Du
Externí odkaz:
http://arxiv.org/abs/2304.02714
Autor:
Li, Pu, Liua, Xiaobai, Palmer, K. J., Fleishman, Erica, Gillespie, Douglas, Nosal, Eva-Marie, Shiu, Yu, Klinck, Holger, Cholewiak, Danielle, Helble, Tyler, Roch, Marie A.
Publikováno v:
in Intl. Joint Conf. Neural Net. (Glasgow, Scotland, July 19-24), pp. 10 (2020)
We present a learning-based method for extracting whistles of toothed whales (Odontoceti) in hydrophone recordings. Our method represents audio signals as time-frequency spectrograms and decomposes each spectrogram into a set of time-frequency patche
Externí odkaz:
http://arxiv.org/abs/2005.08894
Autor:
Bianco, Michael J., Gerstoft, Peter, Traer, James, Ozanich, Emma, Roch, Marie A., Gannot, Sharon, Deledalle, Charles-Alban
Publikováno v:
Journal of the Acoustical Society of America, 146(5) pp.3590--3628, 2019
Acoustic data provide scientific and engineering insights in fields ranging from biology and communications to ocean and Earth science. We survey the recent advances and transformative potential of machine learning (ML), including deep learning, in t
Externí odkaz:
http://arxiv.org/abs/1905.04418
Objective of this work is to integrate high performance computing (HPC) technologies and bioacoustics data-mining capabilities by offering a MATLAB-based toolbox called Raven-X. Raven-X will provide a hardware-independent solution, for processing lar
Externí odkaz:
http://arxiv.org/abs/1610.03772
Autor:
ROCH, MARIE-HÉLÈNE
Publikováno v:
Vie des Arts; 2024, Vol. 69 Issue 276, p52-57, 6p, 5 Color Photographs
Autor:
Simonis, Anne E., Roch, Marie A., Bailey, Barbara, Barlow, Jay, Clemesha, Rachel E. S., Iacobellis, Sam, Hildebrand, John A., Baumann-Pickering, Simone
Publikováno v:
Marine Ecology Progress Series, 2017 Aug . 577, 221-235.
Externí odkaz:
https://www.jstor.org/stable/26403697
Akademický článek
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Publikováno v:
In Theriogenology 15 January 2017 88:174-182
Akademický článek
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