2010 Fiscal Year Final Research Report
Research of classification methods of hyper-spectral data, elucidation of the theoretical nature and applications to real data
| Project/Area Number |
19300096
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | Kyushu University |
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Principal Investigator |
NISHII Ryuei Kyushu University, 大学院・数理学研究院, 教授 (40127684)
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| Co-Investigator(Kenkyū-buntansha) |
KONISHI Sadanori 中央大学, 理工学部, 教授 (40090550)
SAKATA Toshio 九州大学, 芸術工学研究院, 教授 (20117352)
QIN Pan 九州大学, 数理学研究院, 学術研究員 (40532718)
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| Co-Investigator(Renkei-kenkyūsha) |
NINOMIYA Yoshiyuki 九州大学, 数理学研究院, 准教授 (50343330)
MASUDA Hiroki 九州大学, 数理学研究院, 准教授 (10380669)
TANAKA Shojiro 島根大学, 総合理工学部, 教授 (00197427)
SHIMIZU Kunio 慶應義塾大学, 理工学部, 教授 (60110946)
EGUCHI Shinto 統計数理研究所, 教授 (10168776)
UCHIDA Masayuki 大阪大学, 大学院・基礎工学研究科, 教授 (70280526)
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| Project Period (FY) |
2007 – 2010
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| Keywords | パターン認識 / 学習理論 / 時空間現象 / 統計モデリング / 多重分光画像 |
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| Research Abstract |
Recently, classification methods applicable to hyper-dimensional data are required. We proposed a bagging-type AdaBoost method, which can give complicated decision boundaries and avoid over learning. Classification methods and regression problems related to geo-spatial data, and unmixing of land-cover categories were also studied through modeling of spatial dependency by Markov random fields. Furthermore, we published a book discussing information criteria for statistical model selection.
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Research Products
(42 results)
