2023 Fiscal Year Research-status Report
Tackling real-world time series using dynamic neural networks
| Project/Area Number |
23K16949
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| Research Institution | Kyushu University |
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Principal Investigator |
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| Project Period (FY) |
2023-04-01 – 2025-03-31
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| Keywords | Time series / Temporal neural network / Dynamic programming |
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| Outline of Annual Research Achievements |
This research resulted in many international publications. There were three international journal and five international conference presentations. Of the publications, two were in one of the top international journals in the proposals field, Pattern Recognition. The international conference papers were peer-reviewed and were part of many top conferences, such as ICCV and ICDAR. In addition, I have collaborated with interdisciplinary fields such as remote sensing, bioinformatics, and natural language processing.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
This research had success in many areas including feature representation, generation, and adversarial attacks.
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| Strategy for Future Research Activity |
The research will continue as planned. In addition, new collaborations and additional research topics will be developed. There are multiple papers under review by myself and my students.
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| Causes of Carryover |
This coming year will have many in person conferences, thus the grant will be used.
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