| Paper Abstract and Keywords |
| Presentation |
2025-06-30 15:50
Slope Change Detection using Multiple Instance Learning and Memory Banks from Remote Surveillance Cameras
Kohei Takashima, Yota Yamamoto, Yukinobu Taniguchi (Tokyo Univ of Science) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Landslides are serious natural disasters that cause extensive damage to human lives and social infrastructure. Preventing large-scale disasters requires accurate detection of slight slope changes, such as surface collapse and avalanches. This paper proposes a method for detecting slope changes using deep learning from an image sequence taken with surveillance cameras at one-hour intervals. The proposed method utilizes Multiple Instance Learning (MIL) to learn slope change detection models with ground-truth labels (presence/absence of changes) assigned to each image instead of each pixel. To suppress false positives due to temporary weather and lighting changes, the proposed method retrieves the feature map most similar to the current frame from a memory bank, which accumulates feature maps over the past few days, and compares it with the current feature map. We conducted experiments using a dataset of one year's worth of surveillance camera images, confirming that the accuracy of slope change detection surpasses that of conventional methods. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
deep learning / multiple instance learning / anomaly detection / change detection / landslide detection / / / |
| Reference Info. |
ITE Tech. Rep., vol. 49, pp. 11-14, June 2025. |
| Paper # |
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| Date of Issue |
2025-06-23 (AIT) |
| ISSN |
Online edition: ISSN 2424-1970 |
| Download PDF |
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| Conference Information |
| Committee |
IIEEJ AIT |
| Conference Date |
2025-06-30 - 2025-07-01 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
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| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
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| Paper Information |
| Registration To |
IIEEJ |
| Conference Code |
2025-06-IIEEJ-AIT |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Slope Change Detection using Multiple Instance Learning and Memory Banks from Remote Surveillance Cameras |
| Sub Title (in English) |
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| Keyword(1) |
deep learning |
| Keyword(2) |
multiple instance learning |
| Keyword(3) |
anomaly detection |
| Keyword(4) |
change detection |
| Keyword(5) |
landslide detection |
| Keyword(6) |
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| Keyword(7) |
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| Keyword(8) |
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| 1st Author's Name |
Kohei Takashima |
| 1st Author's Affiliation |
Tokyo University of Science (Tokyo Univ of Science) |
| 2nd Author's Name |
Yota Yamamoto |
| 2nd Author's Affiliation |
Tokyo University of Science (Tokyo Univ of Science) |
| 3rd Author's Name |
Yukinobu Taniguchi |
| 3rd Author's Affiliation |
Tokyo University of Science (Tokyo Univ of Science) |
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| Speaker |
Author-1 |
| Date Time |
2025-06-30 15:50:00 |
| Presentation Time |
20 minutes |
| Registration for |
IIEEJ |
| Paper # |
AIT2025-170 |
| Volume (vol) |
vol.49 |
| Number (no) |
no.18 |
| Page |
pp.11-14 |
| #Pages |
4 |
| Date of Issue |
2025-06-23 (AIT) |