Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2025: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2024: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2023: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
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Outline of Research at the Start |
The unique features in this study are: (1) on-line feature selection from data stream using incremental learning on multiclass classification, (2) the fusion of different cross layered CNN and multiclass classifiers collectively representing features extraction of different health symptoms running on GPUs for leaning and testing (3) Ensemble of different deep semi-supervised leaners to predict early health risks, all employing: (a) robust real-time on-line semi-supervised learning systems, and (b) generative Neural Network (GAN) for raw data: for health risk predictions of high accuracy.
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