JpGU Meeting 2020
Session outline| Solid Earth Sciences(S) | ||
|---|---|---|
| Session Sub-category | Complex & General(CG) | |
| Session ID | S-CG60 | |
| Title | Toward Discoveries in Solid Earth Sciences by Machine Learning | |
| Short Title | Machine Learning in Solid Earth Sciences | |
| Main Convener | Name | Takahiko Uchide |
| Affiliation | Research Institute of Earthquake and Volcano Geology, Geological Survey of Japan, National Institute of Advanced Industrial Science and Technology (AIST) | |
| Co-Convener 1 | Name | Yuki Kodera |
| Affiliation | Meteorological Research Institute, Japan Meteorological Agency | |
| Co-Convener 2 | Name | Hisahiko Kubo |
| Affiliation | National Research Institute for Earth Science and Disaster Resilience | |
| Session Language | E | |
| Scope | The recent development of the machine learning techniques including the deep learning is leading innovations in various fields. The applications of these techniques, for example, the classification, the pattern recognition, and the regression of data, to solid earth sciences are also now under development. 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. In particular, we encourage contributions which made discoveries in solid earth sciences. We also look forward to studies addressing the black box issue of the deep learning. | |
| Presentation Format | Oral and Poster presentation | |