Updated on 2024/12/19

写真a

 
Chao Jinhui
 
Organization
Faculty of Science and Engineering Professor
Other responsible organization
Information and System Engineering Course of Graduate School of Science and Engineering, Master's Program
Electrical Engineering and Information Systems Course of Graduate School of Science and Engineering, Doctoral Program
Contact information
The inquiry by e-mail is 《here
External link

Degree

  • 工学博士 ( 東京工業大学 )

Research History

  • 1996.4 -  

    中央大学理工学部教授

  • 1992.4 - 1996.3

    中央大学理工学部助教授

  • 1989.10 - 1992.3

    東京工業大学電気電子工学科助手

Professional Memberships

  • 電子情報通信学会

  • IEEE

  • EUSIP

  • IACR

  • NOLTA

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Papers

  • Definition and Estimation of Dimension in Facial Expression Space Reviewed

    Masashi Shinto, Reiner Lenz, Jinhui Chao

    Human-Computer Interaction. Theory, Methods and Tools. M. Kurosu (Ed.): HCII 2021   LNCS ( 12762 )   604 - 621   2021

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Springer  

    It has recently been shown that the facial expression space as a psychophysical image space is a Riemann space where the metric tensor is defined by the JND discrimination thresholds at every point in the space. The major obstacle to understand this space is how to estimate the metric tensor in high dimensions which requires an inaccessible number of psychophysical experiments. In this paper we address two fundamental issues: methods to estimate the Riemann metric tensor in a high dimensional space and how to define and to determine the effective dimensions of Riemann spaces and psychophysical spaces. We introduce new definitions for these dimensions and novel algorithms for estimating the high dimensional Riemann metric tensor and for dimension reduction to low dimensional subspaces. We apply these algorithms to the facial expressions space. The Riemann metric tensor of the high dimensional facial expression space is estimated from psychophysical measurements of JND data. We apply these methods to investigate the facial expression space. We estimate the effective dimension (together with upper and lower bounds) of Riemann manifolds and psychophysical spaces.

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  • A New Algorithm to Find Isometric Maps for Comparison and Exchange of Facial Expression Perceptions Reviewed

    Masashi Shinto, Jinhui Chao

    Human-Computer Interaction. Theory, Methods and Tools. M. Kurosu (Ed.): HCII 2021   LNCS ( 12762 )   592 - 603   2021

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Springer  

    Recently transformations between psychophysical spaces of different individuals found applications in various perceptional studies such as color science and facial expressions. These spaces are known to be Riemann spaces of which the Riemann metric tensor is defined by JND discrimination thresholds at every point. In particular, a map between these spaces preserving subjective differences is called an isometry or distance-preserving map. Until now, algorithms to compute such a map assumed the Riemann metric tensor or hyperellipsoids of JND thresholds, therefore demand a large number of measurements. They can only obtain an isometry in a restricted form without uniqueness and difficult to apply to high dimensions. In this paper, we propose a new algorithm to compute a local isometry in general form without restrictions between Riemann/psychophysical spaces. We only need JND threshold data points more than the dimension of the space by solving a linear equation system which achieves uniqueness of the solution and statistical /numerical stability. We apply the algorithm to shown examples for comparison and exchange between facial expression perceptions of different observers.

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  • Dimension Estimation and Topological Manifold Learning Reviewed

    Hajime Tasaki, Reiner Lenz, Jinhui Chao

    Proceedings of IJCNN 2019 - International Joint Conference on Neural Networks   ( N-19673 )   2019.7

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:978-1-7281-2009-6/$31.00 ©2019 IEEE  

    We describe a framework which can be used to investigate the geometrical structure of datasets in high-dimensional spaces. Understanding these geometrical properties
    is essential in machine learning in general. An application which
    has received much attention recently is the investigation of adversarial examples which can be easily identified by humans
    but which are misleading neural networks.
    . We argue that a key concept in the analysis is the dimension
    of a manifold. Many machine learning methods use dimension
    reduction techniques to understand or classify the input data
    We point out different definitions of a dimension of a manifold. We use tools from the theory of topological manifolds to introduce local, or intrinsic and global dimensions. We introduce a framework for dimension estimation and topological manifold learning based on the measure ratio method to estimate the dimensions and structure of the data manifold. As
    an illustration we use images of handwritten digits and points of
    a Klein-bottle embedded in a five-dimensional space. We compare
    the results obtained by the measure ratio method with the well-known local-principal component analysis estimation.

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  • How to Compare and Exchange Facial Expression Perceptions Between Different Individuals with Riemann Geometry Reviewed

    Masaki Shinto, Jinhui Chao

    Human-Computer Interaction. Recognition and Interaction Technologies} M. Kurosu (Ed.): HCII 2019   LNCS ( 11567 )   155 - 167   2019

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Springer  

    Facial expression recognition has been a major theme in
    researches of human-centric science and technology. An open question
    remained is that it is difficult to find an objective representation for
    facial expressions so that one can compare perceptions between differ ent individuals. It is partially due to that psychological spaces of facial
    expressions until now were built from subjective evaluations such as SD
    score or Affective grid, in which it is difficult to find correspondence
    between physical stimuli and psychological responses. Recently, Sumiya
    et al. built a psychophysical facial expression space by measuring JND
    thresholds in the facial image space, which define the space as a Rie mann manifold [7]. In this paper, we present algorithms to compare and
    exchange facial expression perceptions between individuals using isome try or a distance-preserving map between the Riemann spaces.

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  • Transform Facial Expression Space to Euclidean Space Using Riemann Normal Coordinates and Its Applications Reviewed

    Runa Sumiya, Jinhui Chao

    Human-Computer Interaction. Recognition and Interaction Technologies M. Kurosu (Ed.): HCII 2019   LNCS ( 11567 )   168 - 178   2019

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Springer  

    It is reported recently in [1] on construction of the psychophysical space of facial expressions through measurement of JND thresholds in the space. It is shown that the facial expression space is, in fact, not a Euclidean space but a Riemann space of which the Riemann metric is defined by the JND thresholds. In this paper, we shown how to transform the facial expression space to Euclidean space in a way to preserve geometry such as distances and angles in the Riemannian space. We build the Riemann normal coordinate system in the facial expression
    space, which can be regarded as a generalized polar coordinate system
    consisted of geodesics emanating from the origin and concentric circles
    with the radius measured by geodesic distances. Results by applying the
    above method to the JND data in [1] are shown together with application
    to expression recognition.

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Books

  • 暗号理論と楕円曲線

    辻井重男, 笠原正雄編著( Role: Joint author)

    森北出版  2008.9 

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    Total pages:251   Responsible for pages:61   Language:Japanese   Book type:Scholarly book

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  • 情報セキュリティー暗号・認証・倫理まで

    辻井重男, 笠原正雄( Role: Joint author)

    昭晃堂  2003.1 

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    Total pages:213   Responsible for pages:8   Language:Japanese   Book type:Scholarly book

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  • 「情報工学辞典」「楕円曲線」

    趙晋輝( Role: Joint author)

    2001.4 

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    Language:Japanese   Book type:Dictionary, encyclopedia

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  • 適応信号処理(209p.) 5, 6章分担

    辻井, 久保田, 古川( Role: Sole author)

    昭晃堂  1995.4 

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    Language:Japanese   Book type:Scholarly book

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  • 第5章、適応アルゴリズムの拡張、第1節 跳躍アルゴリズム、第6章、ニューラルネットワーク

    井重( Role: Sole author)

    昭晃堂  1995.4 

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    Responsible for pages:107-113,145-207   Language:Japanese   Book type:Scholarly book

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MISC

  • R.Avanzi, C.Doche, T.Lange, K.Nguyen and F. Vercauteren : Handbook of hyperelliptic curve cryptography. Reviewed

    趙晋輝, 松尾和人, 百瀬文之

    数学   61 ( 4 )   433 - 436   2009.10

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    Language:Japanese   Publishing type:Book review, literature introduction, etc.  

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  • Recent topics on hyperelliptic cryptography Invited Reviewed

    Jinhui Chao

    RIMS Kokyuroku, Kyoto University ''Algebraic Aspects of Coding Theory and Cryptography"   1420   174 - 182   2005.4

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    Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)  

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  • 代数曲線上の公開鍵暗号 Invited Reviewed

    松尾和人, 有田正剛

    情報処理、特集「電子社会を推進する暗号技術」   45 ( 11 )   1114 - 1116   2004.11

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    Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)  

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  • 代数曲線暗号 Reviewed

    松尾和人, 有田剛, 趙晋輝

    日本応用数理学会論文誌   13 ( 2 )   231 - 243   2003.2

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    Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)   Publisher:The Japan Society for Industrial and Applied Mathematics  

    This paper is a survey on the state-of-the-art of cryptosystems based on the discrete logarithm over algebraic curves on finite fields. The issue on security of these systems against various attacks are firstly considered. Then fast addition algorithms and efficient point counting algorithms for Jacobian varieties of algebraic curves are discussed. These algorithms, although are necessary for construction of algebraic curve cryptosystems, had not been available until very recently. This paper also surveys the known results and the recent advances of related number theoretic algorithms and new developments in construction of algebraic curve cryptosystems.

    DOI: 10.11540/jsiamt.13.2_231

    CiNii Books

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  • 情報通信工学における群論と不変量理論' Invited

    趙晋輝

    電子情報通信学会学会誌(解説論文)   Vol.84 ( No.6 )   379 - 383   2001.6

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    Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)  

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Presentations

  • GHS攻撃の対象となる被覆曲線を持つ楕円曲線の同型類に関する考察」|rn|ISEC2015、3月2日

    細萱, 飯島, 志村, 趙

    電子情報通信学会情報セキュリティ研究会  2015.3 

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    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

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  • 色弁別閾値を用いた個人認証方式

    小田倉健介, 趙晋輝

    バイオメトリックス研究会 (BioX)  2015.3 

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    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

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  • URL埋め込み型クロスサイトスクリプティング攻撃の特徴検出

    海寳貴人, 松田 健, 園田道夫, 趙 晋輝

    情報処理学会第77回全国大会 6S-04  2015.3 

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  • 線形分類器によるクロスサイトスクリプティング(XSS)の検知に関する考察

    梅原章宏, 松田 健, 園田道夫, 趙 晋輝

    情報処理学会第77回全国大会 6S-05  2015.3 

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  • 潜在曲線を用いた着色によるSQLインジェクション攻撃の特徴の可視化

    藤岡あやか, 松田 健, 園田道夫, 趙 晋輝

    情報処理学会第77回全国大会 6S-06  2015.3 

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Awards

  • IEICE Milestone

    2017.5   IEICE   色弁別閾値を基準とした新しい色弱補正法の提案

    望月理香, 中村竜也, 趙晋輝

  • 電子情報通信学会フェロー

    2013.6   電子情報通信学会   楕円・超楕円暗号理論と色彩情報処理の先駆的研究

    趙晋輝

  • 情報処理学会優秀論文賞

    2013.6   情報処理学会   "k-匿名化手法の効率向上に関する一提案|rn|情報処理学会 第75回全国大会講演論文集 2Z2, p.3-514, 2013."

    渡邉奈津美, 土井洋, 趙 晋輝

  • 喜安善市賞

    2011.6   電子情報通信学会   "「色弁別閾値を基準とした新しい色弱補正法の提案」|rn|電子情報通信学会論文誌 Vol.J94-A, No.2, pp.127-137, Feb. 2011."

    望月理香, 中村竜也, 趙晋輝

  • 電子情報通信学会論文賞

    2011.6   電子情報通信学会   "「色弁別閾値を基準とした新しい色弱補正法の提案」|rn|電子情報通信学会論文誌 Vol.J94-A, No.2, pp.127-137, Feb. 2011."

    望月理香, 中村竜也, 趙晋輝

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Research Projects

  • 楕円曲線に基づく安定性の高い暗号システムに関する研究

    1997.4 - 1999.3

    文部科学省  科学研究費補助金(基盤研究C2) 

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    Grant type:Competitive

    Grant amount: \2700000

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  • 安定性と大域収束性を保証する新しいIIR型適応信号処理アルゴリズムに関する研究

    1996.4 - 1997.3

    文部科学省  科学研究費補助金(基盤研究C2) 

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    Grant type:Competitive

    Grant amount: \1300000

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  • 大域的な収束性と汎化能力を保障する多層人工神経回路網の新しい学習方式に関する研究

    1994.4 - 1995.3

    文部科学省  科学研究費補助金(一般研究C) 

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    Grant type:Competitive

    Grant amount: \1100000

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