Evolutionary automatic construction of cellular networks for image processing and recognition
| Project/Area Number |
26280056
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Partial Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Perceptual information processing
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| Research Institution | Yokohama National University |
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Principal Investigator |
NAGAO TOMOHARU 横浜国立大学, 大学院環境情報研究院, 教授 (10180457)
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥16,380,000 (Direct Cost: ¥12,600,000、Indirect Cost: ¥3,780,000)
Fiscal Year 2016: ¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2015: ¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2014: ¥7,540,000 (Direct Cost: ¥5,800,000、Indirect Cost: ¥1,740,000)
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| Keywords | 知能情報処理 / 進化計算法 / 人工知能 / 機械学習 / 画像処理 / 画像認識 / セル型回路 / 遺伝的アルゴリズム / 画像、文章、音声等認識 / アルゴリズム / システムオンチップ |
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| Outline of Final Research Achievements |
The way to perform image processing and recognition using the cellular network which arranged a small-scale circuit which consists of rather simple functions in lattice grid has been researched in this project. In this method, evolutional computation, which is a kind of optimization, was employed to construct the adequate cellular network for a given task automatically. We applied the method to the tasks such as super-resolution, image segmentation and semantic segmentation and so on, and verified the effectiveness of the method. This method has a big advantage that it is possible to construct various processing just by determining a small-scale circuit, and the method is also practical.
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Report
(4 results)
Research Products
(26 results)
