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Twist-State Classifier for Floating Marine Biomass Based on Physical Simulation

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Intelligent Autonomous Systems 13

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 302))

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Abstract

This paper describes new approaches for classifying twist of seaweeds. There are no evaluation measures of the twist formation of complicated objects quantitatively because the definition of a qualitative twist is a difficult problem. The twist of seaweeds is one of these problems. In this paper, we propose three factors (physical, geometric, and time factor of twist) for characterizing the twist state, and we develop the twist-state classifier based on these factors. Additionally, the analysis experiment verifies how the classifier shows the classification accuracy of twist state.

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Author information

Authors and Affiliations

  1. Hokkaido University, Sapporo, Japan

    Jun Ogawa, Hiroyuki Iizuka & Masahito Yamamoto

  2. Hokkaido Information University, Ebetsu, Japan

    Masashi Furukawa

Authors
  1. Jun Ogawa
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  2. Hiroyuki Iizuka
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  3. Masahito Yamamoto
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  4. Masashi Furukawa
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Corresponding author

Correspondence to Jun Ogawa .

Editor information

Editors and Affiliations

  1. Information Engineering, University of Padua, Padua, Italy

    Emanuele Menegatti

  2. Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

    Nathan Michael

  3. Fachbereich Informatik, Technische Universität Kaiserslautern Arbeitsgruppe Robotersysteme, Kaiserslautern, Germany

    Karsten Berns

  4. Integrated Information Technology, Aoyama Gakuin University, Tokyo, Japan

    Hiroaki Yamaguchi

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© 2016 Springer International Publishing Switzerland

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Ogawa, J., Iizuka, H., Yamamoto, M., Furukawa, M. (2016). Twist-State Classifier for Floating Marine Biomass Based on Physical Simulation. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds) Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-319-08338-4_59

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  • DOI: https://doi.org/10.1007/978-3-319-08338-4_59

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08337-7

  • Online ISBN: 978-3-319-08338-4

  • eBook Packages: EngineeringEngineering (R0)

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