| Project/Area Number |
24KJ0755
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| Research Category |
Grant-in-Aid for JSPS Fellows
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| Allocation Type | Multi-year Fund |
|---|
| Section | 国内 |
|---|
| Review Section |
Basic Section 61020:Human interface and interaction-related
|
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| Research Institution | The University of Tokyo |
|---|
Principal Investigator |
蘇 子雄 東京大学, 大学院情報学環・学際情報学府, 特別研究員(DC2)
|
|---|
| Project Period (FY) |
2024-04-23 – 2026-03-31
|
| Project Status |
Granted (Fiscal Year 2024)
|
| Budget Amount *help |
¥1,500,000 (Direct Cost: ¥1,500,000)
Fiscal Year 2025: ¥400,000 (Direct Cost: ¥400,000)
Fiscal Year 2024: ¥1,100,000 (Direct Cost: ¥1,100,000)
|
|---|
| Outline of Research at the Start |
This research proposes to enhance Human-Computer Interaction with self-supervised learning to allow AI systems to adapt in real-world settings without extensive user input, focusing on multimodal activity recognition and addressing issues including data imbalance and domain generalization.
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