novel probability Pattern Recognition derived from a density function consisting with normal samples and their mirror ones
| Project/Area Number |
24500338
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | Tokyo University of Agriculture and Technology |
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Principal Investigator |
SEIJI Hotta 東京農工大学, 工学(系)研究科(研究院), 准教授 (90346932)
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2014: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2013: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2012: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
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| Keywords | パターン認識 / 部分空間法 / Pattern Recognition |
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| Outline of Final Research Achievements |
This research presents a novel probability density function (PDF) consisting with normal samples and their mirror ones. We can derive heuristic classifiers such as simple and multiple subspace classifiers from this PDF. The performance of our approach is verified by experiments on big data recognition such as image, audio, and video.
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Report
(4 results)
Research Products
(15 results)
