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Yushi Moko

Portrait

Affiliation

Project Academic Support Staff
Data Science Research Division,
Information Technology Center, University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
Phone: +81.3.5841.0224 (laboratory)
Fax: +81.3.5841.6952
Email: moko

Research Theme

Image Recognition with Computer Graphics Technology
Active sensing technology in high-speed mobile environments
Parallel Processing and High-Speed Storage Technologies for High-Speed Video

Publications

Papers

  • Yuki Kubota, Yushan Ke, Tomohiko Hayakawa, Yushi Moko, Masatoshi Ishikawa, Optimal Material Search for Infrared Markers under Non-Heating and Heating Conditions, Sensors, Vol.21, Issue 19, Article No.6527, pp.1-17 (2021)

Review Papers

  • Tomohiko Hayakawa, Yushi Moko, Masatoshi Ishikawa, Yoshimasa Ohnishi, Hiroyuki Kameoka:[Minister's Award] High-resolution deformation detection method for lining concrete at 100 km/h, Journal of Civil Engineering, vol.62, no.7, p.146 (2021)
  • Tomohiko Hayakawa, Yuki Kubota, Yushi Moko, Yushan Ke, and Masatoshi Ishikawa: High-speed Imaging Technology Using Motion-blur Compensation for Infrastructure Inspection, Japanese Journal of Optics, Vol. 50, No. 2, pp. 61-67 (2021)

International Conference

  • Yuriko Ezaki, Yushi Moko, Haruka Ikeda, Tomohiko Hayakawa and Masatoshi Ishikawa:Extension of the Capture Range Under High-Speed Motion Using Galvanometer Mirror, 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (Virtual Conference, 2020.7.9), pp.1854-1859.
  • Y. Kubota, T. Hayakawa, Y. Ke, Y. Moko, M. Ishikawa: High-speed motion blur compensation system in infrared region using galvanometer mirror and thermography camera, SPIE Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020 (Anaheim, 2020.4.) / Proceedings, 1137919.
  • T. Hayakawa, Y. Moko, K. Morishita, and M. Ishikawa: Real-time Robust Lane Detection Method at a Speed of 100 km/h for a Vehicle-mounted Tunnel Surface Inspection System, 2019 IEEE Sensors Applications Symposium (2019).
  • Tomohiko Hayakawa, Yushi Moko, Kenta Morishita, and Masatoshi Ishikawa: Real-time Robust Lane Detection Method at a Speed of 100 km/h for a Vehicle-mounted Tunnel Surface Inspection System, 2019 IEEE Sensors Applications Symposium (SAS2019) (Sophia Antipolis, 2019.3.11)
  • Tomohiko Hayakawa, Yushi Moko, Kenta Morishita and Masatoshi Ishikawa, "Pixel-Wise Deblurring Imaging System Based on Active Vision for Structural Health Monitoring at a Speed of 100 km/h," 2017 The 10th International Conference on Machine Vision(Vienna, Austria, 2017.11.14)/ (Oral Session)
  • Takeoka, H., Moko, Y., Reynolds, C., Komuro, T., Watanabe, Y., and Ishikawa, M. (2011). VolVision: High-speed Capture in Unconstrained Camera Motion. The 4th ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia (SIGGRAPH ASIA 2011).
  • Yushi Moko, Yoshihiro Watanabe, Takashi Komuro, Masatoshi Ishikawa, Masami Nakajima, Kazutami Arimoto: Implementation and evaluation of FAST corner detection on the massively parallel embedded processor MX-G, The Seventh IEEE Workshop on Embedded Computer Vision/Proceedings, pp.157-162

Domestic Conference

  • Tomohiko Hayakawa, Yushan Ke, Yushi Moko, and Masatoshi Ishikawa:Illumination requirements for traveling inspection vehicles using motion blur compensated imaging -towardsimaging tunnel linning on highways-, 42nd Annual Conference of IEIJ Tokyo Branch (Online, 2020.12.9) Proceedings, pp. B-6:1-B-6:2. Best Presentation Award
  • Tomohiko Hayakawa, Yushi Moko, Kenta Morishita, and Masatoshi Ishikawa:Real-time Robust Lane Detection Method at a Speed of 100 km/h for Vehicle-mounted Tunnel Surface Inspection System, 16th ITS Symposium(Kyoto, 14th December, 2018), 4-B-01, 2018. Best Poster Award
  • Yushi Moko, Yoshihiro Watanabe, Takashi Komuro, Masatoshi Ishikawa: Pose estimation of 3D objects using CG and GPU, Meeting on Image Recognition and Understanding 2009, pp.1653-1660, 2009.
Ishikawa Group Laboratory, Data Science Research Division, Information Technology Center, University of Tokyo / Tokyo University of Science
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