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Ken Yoda

Showing results (31-40 of 47) with videos related to

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Communications Biology|October 31, 2020
Machine learning enables improved runtime and precision for bio-loggers on seabirdsJoseph Korpela, Hirokazu Suzuki, Sakiko Matsumoto, et al.
Scientific Reports|May 26, 2021
Mapping marine debris encountered by albatrosses tracked over oceanic watersBungo Nishizawa, Jean-Baptiste Thiebot, Fumio Sato, et al.
Scientific Reports|December 4, 2015
Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast systemYasumasa Miyazawa, Xinyu Guo, Sergey M Varlamov, et al.
Ecology and Evolution|December 17, 2024
Three-Dimensional Vascular Structure of Caudal and Dorsal Fins of a Dwarf Sperm WhaleTaro Okamura, Ashley R Smith, Tomoyuki Mikami, et al.
Proceedings of the National Academy of Sciences of the United States of America|October 4, 2022
Pelagic seabirds reduce risk by flying into the eye of the stormEmmanouil Lempidakis, Emily L C Shepard, Andrew N Ross, et al.
Proceedings of the National Academy of Sciences of the United States of America|July 27, 2016
Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and directionYoshinari Yonehara, Yusuke Goto, Ken Yoda, et al.
Plos Biology|July 17, 2025
Penguins exploit tidal currents for efficient navigation and opportunistic foragingRichard M Gunner, Flavio Quintana, Mariano H Tonini, et al.
Environmental Science & Technology|June 13, 2013
Contaminants in tracked seabirds showing regional patterns of marine pollutionAtsuo Ito, Rei Yamashita, Hideshige Takada, et al.
Movement Ecology|April 1, 2025
Biologging intelligent Platform (BiP): an integrated and standardized platform for sharing, visualizing, and analyzing biologging dataKatsufumi Sato, Shinichi Watanabe, Takuji Noda, et al.
Nature Communications|October 21, 2020
Deep learning-assisted comparative analysis of animal trajectories with DeepHLTakuya Maekawa, Kazuya Ohara, Yizhe Zhang, et al.
Pageof 5

Showing results (31-40 of 47) with videos related to

Sort By:
Pageof 5
Communications Biology|October 31, 2020
Machine learning enables improved runtime and precision for bio-loggers on seabirdsJoseph Korpela, Hirokazu Suzuki, Sakiko Matsumoto, et al.
Scientific Reports|May 26, 2021
Mapping marine debris encountered by albatrosses tracked over oceanic watersBungo Nishizawa, Jean-Baptiste Thiebot, Fumio Sato, et al.
Scientific Reports|December 4, 2015
Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast systemYasumasa Miyazawa, Xinyu Guo, Sergey M Varlamov, et al.
Ecology and Evolution|December 17, 2024
Three-Dimensional Vascular Structure of Caudal and Dorsal Fins of a Dwarf Sperm WhaleTaro Okamura, Ashley R Smith, Tomoyuki Mikami, et al.
Proceedings of the National Academy of Sciences of the United States of America|October 4, 2022
Pelagic seabirds reduce risk by flying into the eye of the stormEmmanouil Lempidakis, Emily L C Shepard, Andrew N Ross, et al.
Proceedings of the National Academy of Sciences of the United States of America|July 27, 2016
Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and directionYoshinari Yonehara, Yusuke Goto, Ken Yoda, et al.
Plos Biology|July 17, 2025
Penguins exploit tidal currents for efficient navigation and opportunistic foragingRichard M Gunner, Flavio Quintana, Mariano H Tonini, et al.
Environmental Science & Technology|June 13, 2013
Contaminants in tracked seabirds showing regional patterns of marine pollutionAtsuo Ito, Rei Yamashita, Hideshige Takada, et al.
Movement Ecology|April 1, 2025
Biologging intelligent Platform (BiP): an integrated and standardized platform for sharing, visualizing, and analyzing biologging dataKatsufumi Sato, Shinichi Watanabe, Takuji Noda, et al.
Nature Communications|October 21, 2020
Deep learning-assisted comparative analysis of animal trajectories with DeepHLTakuya Maekawa, Kazuya Ohara, Yizhe Zhang, et al.
Pageof 5