[S-CG60] Driving Solid Earth Science through Machine Learning

Mon. May 26, 2025 3:30 PM - 5:00 PM 105 (International Conference Hall, Makuhari Messe)

convener:Hisahiko Kubo(National Research Institute for Earth Science and Disaster Resilience), Makoto Naoi(Hokkaido University), Keisuke Yano(The Institute of Statistical Mathematics), Yusuke Tanaka(Geospatial Information Authority of Japan), Chairperson:Yutaro Okada(International Research Institute of Disaster Science), Makoto Naoi(Hokkaido University)

Machine learning (ML) has brought innovations and remarkable results in various science fields including solid earth science. This session provides an opportunity to inspire each other for future developments by bringing studies of ML applications in various fields including solid earth science. We invite a wide range of presentations on ML and related research, from the budding to the more advanced.

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3:30 PM - 4:00 PM

[SCG60-06] Fast and large-scale similar waveform search

★Invited Papers

*Yusuke Matsui¹ (1.The University of Tokyo)

4:00 PM - 4:15 PM

[SCG60-07] Epicenter estimation of tectonic tremors in the nankai subduction zone from a single station using deep learning

*Amane Sugii¹, Yoshihiro Hiramatsu¹ (1.Kanazawa University)

4:15 PM - 4:30 PM

[SCG60-08] B-Value Estimator Using Recurrent Neural Network

*Naofumi Aso¹ (1.Tokyo University of Science)

4:30 PM - 4:45 PM

[SCG60-09] Methodological development of fault slip detection from GNSS using deep learning and application to western Shikoku

*Ryo Nakagawa¹, Yo Fukushima^1,2, Masayuki Kano¹, Keisuke Yano³, Yusuke Tanaka¹, Yutaro Okada², Kazuro Hirahara^4,5 (1.Graduate School of Science and Faculty of Science, Tohoku University, 2.International Research Institute of Disaster Science, Tohoku University, 3.Institute of Statistical Mathematics, 4.RIKEN, 5.Kagawa University)

4:45 PM - 5:00 PM

[SCG60-10] Attempt to extract three-dimensional displacement fields due to fault slip by deep learning technique using InSAR and GNSS data

*Yutaro Okada¹, Yo Fukushima¹ (1.International Research Institute of Disaster Science)

Session information