| Project/Area Number |
21500213
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Sensitivity informatics/Soft computing
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| Research Institution | The University of Electro-Communications |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
HOTTA Kazuhiro 名城大学, 理工学部, 准教授 (40345426)
SHOUNO Hayaru 電気通信大学, 大学院・情報理工学研究科, 准教授 (50263231)
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| Research Collaborator |
RAMESWER Debnathd Khulne University(Bangladesh), Computer Sc. & Engineering Discipline, Professor
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| Project Period (FY) |
2009 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2011: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2010: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2009: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 機械学習 / 画像識別 / 識別モデル / 生成モデル / ランダムフィールド / カーネル / サポートベクトルマシン / ビデオ画像認識 / クラスタリング / 条件付き確率場 / 画像認識 / マルコフランダムフィールド / 二次平均場近似 / 多項式カーネル |
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| Research Abstract |
In machine learning, we have two typical models, i. e., generative and discriminative models. We aimed to combine both of these models in order to obtain more elaborated machine learning models. Two main results are obtained as follows. Firstly, we designed a special discriminative random field and applied it to high performance video image classification. Secondly, we modeled a kernel random field which is constructed as random field with kernels, and successively applied to scene classification.
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