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Multivariate analysis method for biology

Research Project

Project/Area Number 26330194
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Perceptual information processing
Research InstitutionNational Institute of Advanced Industrial Science and Technology (2015-2016)
Wakayama University (2014)

Principal Investigator

Watanabe Kenji  国立研究開発法人産業技術総合研究所, 知能システム研究部門, 研究員 (50571064)

Co-Investigator(Kenkyū-buntansha) 和田 俊和  和歌山大学, システム工学部, 教授 (00231035)
Project Period (FY) 2014-04-01 – 2017-03-31
Project Status Completed (Fiscal Year 2016)
Budget Amount *help
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Keywords多変量解析 / 半教師あり機械学習 / 特徴量変換
Outline of Final Research Achievements

Analysis systems for biological images generally comprise a feature extraction method and a classification method. Task-oriented methods for feature extraction are very effective at improving the classification accuracy. However, it is difficult to utilize such feature extraction methods for versatile task in practice, because few biologists specialize in mathematics and/or informatics to design the task-oriented methods. Thus, in order to improve the usability of these supporting systems, it will be useful to develop a method that can automatically transform the image features of general propose into the effective form toward the task of their interest. In this work, we propose a semi-supervised feature transformation method, which is formulated as a natural coupling of principal component analysis and linear discriminant analysis. Compared with other feature transformation methods, our method showed favorable classification performance in biological image analysis.

Report

(4 results)
  • 2016 Annual Research Report   Final Research Report ( PDF )
  • 2015 Research-status Report
  • 2014 Research-status Report

Research Products

(4 results)

All 2016 2015 2014

All Journal Article (2 results) (of which Peer Reviewed: 2 results,  Open Access: 2 results,  Acknowledgement Compliant: 2 results) Presentation (2 results) (of which Int'l Joint Research: 1 results)

  • [Journal Article] Semi-Supervised Feature Transformation for Tissue Image Classification2016

    • Author(s)
      Kenji Watanabe, Takumi Kobayashi, Toshikazu Wada
    • Journal Title

      PLOS ONE

      Volume: 11

    • DOI

      10.1371/journal.pone.0166413

    • Related Report
      2016 Annual Research Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Journal Article] Semi-supervised Component Analysis2015

    • Author(s)
      Kenji Watanabe, Toshikazu Wada
    • Journal Title

      Proceedings of 2015 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

      Volume: - Pages: 3011-3016

    • DOI

      10.1109/smc.2015.524

    • Related Report
      2015 Research-status Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Presentation] Semi-supervised Component Analysis2015

    • Author(s)
      Kenji Watanabe, Toshikazu Wada
    • Organizer
      2015 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
    • Place of Presentation
      Kowloon (Hong Kong)
    • Year and Date
      2015-10-09
    • Related Report
      2015 Research-status Report
    • Int'l Joint Research
  • [Presentation] 計量学習の高速化2014

    • Author(s)
      渡辺顕司
    • Organizer
      第10回 広島画像情報学セミナー
    • Place of Presentation
      広島大学
    • Year and Date
      2014-10-10
    • Related Report
      2014 Research-status Report

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Published: 2014-04-04   Modified: 2018-03-22  

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