研究課題/領域番号 |
21K17829
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研究機関 | 東京大学 |
研究代表者 |
ルイ笠原 純ユネス 東京大学, 大学院工学系研究科(工学部), 特任助教 (20885412)
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研究期間 (年度) |
2021-04-01 – 2023-03-31
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キーワード | Inspection / Domain adaptation / Clustering / Weak supervision |
研究実績の概要 |
This research aims at the automation of the hammering test for the inspection of concrete structures. Supervised learning approaches have the issue that when the concrete structure differs between training and deployment of the system, the performance is degraded (domain gap). Therefore, in this research was proposed a method for selecting only portion of the training data for the considered inspection target. Using a camera, hammering samples located near surface defects are selected to be used for training. Additionally, weakly supervised approaches have also been investigated: such methods require inputs which are easier to provide than regular labels but larger quantities are needed. Therefore, a method to augment weak supervision based on clustering was proposed.
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現在までの達成度 (区分) |
現在までの達成度 (区分)
3: やや遅れている
理由
Day-to-day operations were greatly affected by restrictions related to COVID-19. Additionally, difficulties were encountered when attempting to purchase sensors due to the shortage of electronic components.
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今後の研究の推進方策 |
So far, a training data selection method to deal with the domain gap and a method for weak supervision augmentation were proposed. Weak supervision has the advantage of being easy to provide by humans. Therefore, in the future it is planned to push research towards the establishment of a new framework allowing domain adaptation and weak supervision.
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次年度使用額が生じた理由 |
Day-to-day operations in the past year were perturbed due to the ongoing pandemic. Additionally, the purchase of selected electronic devices was difficult due to the global supply chain issues. Given the gradual relaxation of restrictions related to the prevention of the spread of COVID-19 along with the acclimation to the new normal, it is expected that in the next fiscal year research could be conducted in a smoother fashion.
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