2020 Fiscal Year Annual Research Report
System for Automatic and Real-time Generalization of Catastrophe Maps based on Deep Learning Methods
| Project/Area Number |
19J13500
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| Research Institution | The University of Tokyo |
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Principal Investigator |
郭 直霊 東京大学, 新領域創成科学研究科, 特別研究員(DC2)
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| Project Period (FY) |
2019-04-25 – 2021-03-31
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| Keywords | deep learning / remote sensing / library establishment |
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| Outline of Annual Research Achievements |
The main research topic “System for Automatic and Real-time Generalization of Catastrophe Maps based on Deep Learning Methods” was splitted into different subtopics. For instance: segmentation and super-resolution library establishment, real-time map segmentation application, high accuracy building semantic based on deep learning, the pedestrian trajectory prediction and surveillance, super-resolution integrated method for accuracy pattern recognition accuracy enhancement, change detection, etc.
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| Research Progress Status |
令和2年度が最終年度であるため、記入しない。
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| Strategy for Future Research Activity |
令和2年度が最終年度であるため、記入しない。
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Research Products
(3 results)
