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NGUYENTUAN CUONG  NGUYENTUAN CUONG

Researcher Number 10814246
Other IDs
  • ORCIDhttps://orcid.org/0000-0003-2556-9191
Affiliation (based on the past Project Information) *help 2022: 東京農工大学, 工学(系)研究科(研究院), 特任助教
2021: 東京農工大学, 工学(系)研究科(研究院), 特任准教授
2018 – 2020: 東京農工大学, 工学(系)研究科(研究院), 特任助教
Review Section/Research Field
Principal Investigator
Basic Section 61010:Perceptual information processing-related
Except Principal Investigator
Medium-sized Section 61:Human informatics and related fields
Keywords
Principal Investigator
mathematical expression / handwriting / clustering / deep metric learning / クラスタリング / 手書き数式 / Seq2Seq / 距離学習 / Minimum Spanning Tree / Graph Neural Networks … More / Transformer / Similarity / structural data / sequential data / semi-supervised learning / dissimilarity / CNN / hierarchical features / weakly supervised / handwriting recognition / mathematical expressions / handwritten answers / sequence to sequence / generative sequence / offline handwriting / online handwriting … More
Except Principal Investigator
アテンション / 深層ニューラルネットワーク / 文脈処理 / 構造解析 / 手書き数式認識 Less
  • Research Projects

    (3 results)
  • Co-Researchers

    (1 People)
  •  Deep metric learning through local attention and generative lossPrincipal Investigator

    • Principal Investigator
      NGUYENTUAN CUONG
    • Project Period (FY)
      2021 – 2022
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 61010:Perceptual information processing-related
    • Research Institution
      Tokyo University of Agriculture and Technology
  •  Enhancement of handwritten mathematical expression recognition through establishment of multi-dimensional structural analysis

    • Principal Investigator
      Nakagawa Masaki
    • Project Period (FY)
      2019 – 2022
    • Research Category
      Grant-in-Aid for Scientific Research (A)
    • Review Section
      Medium-sized Section 61:Human informatics and related fields
    • Research Institution
      Tokyo University of Agriculture and Technology
  •  A Sequence-to-sequence Model based Dissimilarity Measurement for Clustering Structural DataPrincipal Investigator

    • Principal Investigator
      NGUYENTUAN CUONG
    • Project Period (FY)
      2018 – 2020
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 61010:Perceptual information processing-related
    • Research Institution
      Tokyo University of Agriculture and Technology
  • 1.  Nakagawa Masaki (10126295)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results

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