| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Outline of Final Research Achievements |
In this research, we developed a novel technique that constructs efficient image feature extraction process by using a black-box optimization method based on combinatorial optimization of basic image processing units such as image processing filters. Further, we extended and applied the idea of this technique to convolutional neural networks (CNN) that show high performance on image recognition tasks. From the numerical experiments of image recognition, we confirmed that the proposed methods outperform the existing CNN based methods.
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