S (Solid Earth Sciences ) » S-CG Complex & General
[S-CG62] Potentiality of Machine Learning in Solid Earth Sciences
Sun. May 26, 2019 3:30 PM - 5:00 PM Poster Hall (International Exhibition Hall8, Makuhari Messe)
convener:Takahiko Uchide(Research Institute of Earthquake and Volcano Geology, Geological Survey of Japan, National Institute of Advanced Industrial Science and Technology (AIST)), Hirokuni Oda(Institute of Geology and Geoinformation, Geological Survey of Japan, AIST)
The recent development of the machine learning techniques including the deep learning is leading innovations in various fields. The applications of these techniques to solid earth sciences are also expected to develop new frontiers by, for example, the classification, the pattern recognition, and the regression of data. On the other hand, there are concerns on the human-interpretability of the deep learning.
This session will provide an opportunity to share the application studies to various fields in solid earth science and inspire each other. We also look forward to studies addressing the black box issue of the deep learning.
*emmy TY CHANG1 (1.Institute of Oceanography, National Taiwan University)
*Takahiko Uchide1 (1.Research Institute of Earthquake and Volcano Geology, Geological Survey of Japan, National Institute of Advanced Industrial Science and Technology (AIST))
*Liping Fan1 (1.Institute of Geophysics, China Earthquake Administration)
*Tomohisa Okazaki1, Hirotaka Hachiya1, Naonori Ueda1, Asako Iwaki2, Takahiro Maeda2, Hiroyuki Fujiwara2 (1.Center for Advanced Intelligence Project, RIKEN, 2.National Research Institute for Earth Science and Disaster Resilience)
David Heslop1,2, Andrew Roberts1,2, *Hirokuni Oda2, Xiang Zhao1,2, Richard Harrison3, Adrian Muxworthy4, Pengxiang Hu1,2, Tetsuro Sato2 (1.Australian National University, 2.Institute of Geology and Geoinformation, Geological Survey of Japan, AIST, 3.University of Cambridge, 4.Imperial College London)