[S-CG51] Driving Solid Earth Science through Machine Learning

Sun. May 22, 2022 9:00 AM - 10:30 AM 102 (International Conference Hall, Makuhari Messe)

convener:Hisahiko Kubo(National Research Institute for Earth Science and Disaster Resilience), convener:Yuki Kodera(Meteorological Research Institute, Japan Meteorological Agency), Makoto Naoi(Kyoto University), convener:Keisuke Yano(The Institute of Statistical Mathematics), Chairperson:Masaru Nakano(Japan Agency for Marine-Earth Science and Technology), Shinya Katoh(Disater Prevention Research Institute, Kyoto University), Hisahiko Kubo(National Research Institute for Earth Science and Disaster Resilience)

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 especially welcome studies that have led to the discovery of phenomena and theories in solid earth science. We also look forward to studies on the black box problem of AI and efforts toward explainable AI.

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9:00 AM - 9:15 AM

[SCG51-01] Data Augmentation of Ocean Bathymetry Data by Point Cloud Super-Resolution with Graph Convolution

*MICHIHIRO SHONAI¹, Naoya Irisawa¹, Robert Hubacz¹, Masaaki Iiyama² (1.Ecomott Inc., 2.Shiga Univ.)

9:15 AM - 9:30 AM

[SCG51-02] Applying a machine learning model to quantify the surface ruggedness using high-resolution 3D outcrop model

*Takumu Nakamura¹, Arata Kioka², Yasuhiro Yamada² (1.Department of Earth Resources, Marine and Civil Engineering, Kyushu University, 2.Department of Earth Resources Engineering, Kyushu University)

9:30 AM - 9:45 AM

[SCG51-03] Arrival time picking and Polarity detection using Deep learning for automatically creating a seismic catalog

*Shinya Katoh¹, Yoshihisa Iio², Hiroshi Katao², Masayo Sawada², Kazuhide Tomisaka², Mizushima Rie² (1.Graduate School of Science, Kyoto University., 2.Disater Prevention Research Institute, Kyoto University)

9:45 AM - 10:00 AM

[SCG51-04] Comparison of 1D and 2D CNNs for seismic event classifications ~ applications to volcanic events and tectonic tremor

*Masaru Nakano¹, Daisuke Sugiyama¹ (1.Japan Agency for Marine-Earth Science and Technology)

10:00 AM - 10:15 AM

[SCG51-05] Detection and hypocenter determination of volcanic earthquakes using Machine Learning: Application to Kirishima volcano

*Yohei Yukutake¹, Ahyi KIM² (1.Earthquake Research Institute, University of Tokyo, 2.Yokohama City University)

10:15 AM - 10:30 AM

[SCG51-06] Objective Estimation of Mechanical Plate Boundary by Neural Network

*Eito Nagai¹, Naofumi Aso¹ (1.Tokyo Institute of Technology)

Session information