2022 Fiscal Year Research-status Report
深層学習と圧縮センシングを融合した革新的超低消費電力イメージングシステムの実現
| Project/Area Number |
22K12101
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| Research Institution | Hosei University |
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Principal Investigator |
周 金佳 法政大学, 理工学部, 准教授 (50723392)
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| Co-Investigator(Kenkyū-buntansha) |
谷口 一徹 大阪大学, 大学院情報科学研究科, 准教授 (40551453)
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| Project Period (FY) |
2022-04-01 – 2025-03-31
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| Keywords | Image sensing / Deep learning / Compressive sensing |
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| Outline of Annual Research Achievements |
The following tasks have been finished. 1) proposed a structural sensing pattern based optical coding and the intelligent corresponding measurement coding. One journal paper was submitted. 2) Deep learning technology was applied to detect the key information in the video and then compressed by the M coding system. Two papers were accepted by the International Data Compression Conference.
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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
As planned, the structural sensing pattern based optical coding and the intelligent corresponding measurement coding algorithm was developed and obtained good results. Moreover, the key information extraction algorithm also got good results. We will further improve it.
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| Strategy for Future Research Activity |
This project has three main tasks. The first task was already finished. For the second task, we have extracted the moving object as the key information in FY2022. We plan to further improve the key information extraction algorithms, and apply new algorithm to compress these information. Finally, we will start to design the whole system with power adaptive configuration.
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| Causes of Carryover |
I didn't find the required equipment in FY2022. I will try to find some replacement and buy them in FY2023. The other plan will not be changed.
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Research Products
(3 results)
