| Paper Abstract and Keywords |
| Presentation |
2025-02-19 11:30
[Special Talk]
Advanced Finding Generation AI Based on In-context Learning for Inspection Report Creation
Masaya Sato, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
This paper proposes an automatic findings generation technique based on a Multimodal Large Language Model to enhance the efficiency of bridge maintenance management. The generative AI learns the relationship between distress images and their findings from a few examples and generates findings for desired distress images. To effectively leverage this capability, the proposed method utilizes clustering to select the most relevant past inspection reports for each findings category. This approach also makes the implicit knowledge in engineers' findings creation explicit. Experiments verify that the proposed method successfully reflects the insights of engineers and achieves high-precision findings generation. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Inspection image / large language model / automatic findings generation / multimodal large language model / in-context learning / / / |
| Reference Info. |
ITE Tech. Rep., vol. 49, no. 4, ME2025-31, pp. 149-154, Feb. 2025. |
| Paper # |
ME2025-31 |
| Date of Issue |
2025-02-11 (MMS, ME, AIT, SIP) |
| ISSN |
Online edition: ISSN 2424-1970 |
| Download PDF |
|
| Conference Information |
| Committee |
ME AIT MMS IEICE-IE IEICE-ITS SIP |
| Conference Date |
2025-02-18 - 2025-02-19 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Hokkaido Univ. |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Image Processing, etc. |
| Paper Information |
| Registration To |
ME |
| Conference Code |
2025-02-ME-AIT-MMS-IE-ITS-SIP |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Advanced Finding Generation AI Based on In-context Learning for Inspection Report Creation |
| Sub Title (in English) |
|
| Keyword(1) |
Inspection image |
| Keyword(2) |
large language model |
| Keyword(3) |
automatic findings generation |
| Keyword(4) |
multimodal large language model |
| Keyword(5) |
in-context learning |
| Keyword(6) |
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| Keyword(7) |
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| 1st Author's Name |
Masaya Sato |
| 1st Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
| 2nd Author's Name |
Keisuke Maeda |
| 2nd Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
| 3rd Author's Name |
Ren Togo |
| 3rd Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
| 4th Author's Name |
Takahiro Ogawa |
| 4th Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
| 5th Author's Name |
Miki Haseyama |
| 5th Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2025-02-19 11:30:00 |
| Presentation Time |
10 minutes |
| Registration for |
ME |
| Paper # |
MMS2025-31, ME2025-31, AIT2025-31, SIP2025-31 |
| Volume (vol) |
vol.49 |
| Number (no) |
no.4 |
| Page |
pp.149-154 |
| #Pages |
6 |
| Date of Issue |
2025-02-11 (MMS, ME, AIT, SIP) |