Thu. May 30, 2019 11:50 AM - 12:05 PM

[ACG36-04] Deep-Learning Based Short-Term Prediction Method for Sea Ice Concentration Using Explanatory Variables

*Issei Kawashima¹, Toru Kouyama¹, Ryu Sugimoto¹, Ryosuke Nakamura¹ (1.National Institute of Advanced Industrial Science and Technology)

[A-CG36] Earth & Environmental Sciences and Artificial Intelligence

[J] Oral
｜A (Atmospheric and Hydrospheric Sciences )
| A-CG Complex & General

Thu. May 30, 2019 10:45 AM - 12:15 PM 106 (1F)

convener:Tomohiko Tomita(Faculty of Advanced Science and Technology, Kumamoto University), Ken-ichi Fukui(Osaka University), Daisuke Matsuoka(Japan Agency for Marine-Earth Science and Technology), Satoshi Ono(Kagoshima University), Chairperson:Tomohiko Tomita(Kumamoto University, Faculty of Advanced Science and Technology)

Thu. May 30, 2019 1:45 PM - 2:00 PM

[ACG36-05] Remote sensing of cloud using the deep learning based on three-dimensional radiative transfer

*Hironobu Iwabuchi¹, Ryosuke Masuda¹, K. Sebastian Schmidt^2,3, Alessandro Damiani⁴, Rei Kudo⁵ (1.Graduate School of Science, Tohoku University, 2.Department of Atmospheric and Oceanic Sciences, University of Colorado, 3.Laboratory for Atmospheric and Space Physics, University of Colorado, 4.Center for Environmental Remote Sensing, Chiba University, 5.Meteorological Research Institute, Japan Meteorological Agency)

[A-CG36] Earth & Environmental Sciences and Artificial Intelligence

[J] Oral
｜A (Atmospheric and Hydrospheric Sciences )
| A-CG Complex & General

Thu. May 30, 2019 1:45 PM - 3:15 PM 104 (1F)

convener:Tomohiko Tomita(Faculty of Advanced Science and Technology, Kumamoto University), Ken-ichi Fukui(Osaka University), Daisuke Matsuoka(Japan Agency for Marine-Earth Science and Technology), Satoshi Ono(Kagoshima University), Chairperson:Tomohiko Tomita(Kumamoto University, Faculty of Advanced Science and Technology)

Thu. May 30, 2019 2:15 PM - 2:30 PM

[ACG36-07] Time series prediction of cloud cover using whole-sky images and meteorological elements

*Kazunori Ogohara¹, Teppei Sonoda² (1.School of Engineering, University of Shiga Prefecture, 2.Graduate School of Engineering, University of Shiga Prefecture)

[A-CG36] Earth & Environmental Sciences and Artificial Intelligence

[J] Oral
｜A (Atmospheric and Hydrospheric Sciences )
| A-CG Complex & General

Thu. May 30, 2019 1:45 PM - 3:15 PM 104 (1F)

convener:Tomohiko Tomita(Faculty of Advanced Science and Technology, Kumamoto University), Ken-ichi Fukui(Osaka University), Daisuke Matsuoka(Japan Agency for Marine-Earth Science and Technology), Satoshi Ono(Kagoshima University), Chairperson:Tomohiko Tomita(Kumamoto University, Faculty of Advanced Science and Technology)

Thu. May 30, 2019 2:45 PM - 3:00 PM

[ACG36-09] Identification of ships image on SAR data using machine learning

*Takashi Sonoke¹, Hirohide Demura¹ (1.University of Aizu)

[A-CG36] Earth & Environmental Sciences and Artificial Intelligence

[J] Oral
｜A (Atmospheric and Hydrospheric Sciences )
| A-CG Complex & General

Thu. May 30, 2019 1:45 PM - 3:15 PM 104 (1F)

convener:Tomohiko Tomita(Faculty of Advanced Science and Technology, Kumamoto University), Ken-ichi Fukui(Osaka University), Daisuke Matsuoka(Japan Agency for Marine-Earth Science and Technology), Satoshi Ono(Kagoshima University), Chairperson:Tomohiko Tomita(Kumamoto University, Faculty of Advanced Science and Technology)

Thu. May 30, 2019 12:00 AM - 12:00 AM

[ACG36-P05] Application of deep learning techniques to precipitation guidance in short-term weather predictions

*TAKERU KURAKAMI¹, Kazuyoshi Souma¹, Takashi Miyamoto¹, Takahiko Huruya¹, Jun Magome¹, Hiroshi Ishidaira¹ (1.University of Yamanashi)

[A-CG36] Earth & Environmental Sciences and Artificial Intelligence

[J] Poster
｜A (Atmospheric and Hydrospheric Sciences )
| A-CG Complex & General

Thu. May 30, 2019 3:30 PM - 5:00 PM Poster Hall (International Exhibition Hall8, Makuhari Messe)

convener:Tomohiko Tomita(Faculty of Advanced Science and Technology, Kumamoto University), Ken-ichi Fukui(Osaka University), Daisuke Matsuoka(Japan Agency for Marine-Earth Science and Technology), Satoshi Ono(Kagoshima University)

Sun. May 26, 2019 11:15 AM - 11:30 AM

[SSS04-03] A deep convolutional neural network for localizing and detecting earthquake swarm activity based on full waveforms: Chances, challenges and questions

★Invited Papers

*Marius Kriegerowski^1,2, Gesa Maria Petersen^1,2, Hannes Vasyura Bathke², Matthias Ohrnberger² (1.German Research Centre for Geosciences Potsdam, Germany, 2.Inst. of Geosciences, University of Potsdam, Germany)

[S-SS04] New methods for seismicity characterization

[E] Oral
｜S (Solid Earth Sciences )
| S-SS Seismology

Sun. May 26, 2019 10:45 AM - 12:15 PM 301B (3F)

convener:Francesco Grigoli(ETH-Zurich, Swiss Seismological Service), Aitaro Kato(Earthquake Research Institute, the University of Tokyo), Yosuke Aoki(Earthquake Research Institute, University of Tokyo), Claudio Satriano(Institut de Physique du Globe de Paris), Chairperson:Francesco Grigoli(ETH-Zurich; Swiss Seismological Service)

Sun. May 26, 2019 3:45 PM - 4:00 PM

[STT44-02] Development for upgrading the generalization capability of the seismic damage detection of building based on the deep-learning utilizing aerial photographs

★Invited Papers

*Shohei Naito¹, Hiromitsu Tomozawa², Yuji Mori², Naokazu Monma³, Hiromitsu Nakamura¹, Hiroyuki Fujiwara¹ (1.National Research Institute for Earth Science and Disaster Resilience, 2.Mizuho Information and Research Institute, Inc., 3.Pasco Corporation)

[S-TT44] Airborne surveys and monitoring of the Earth

[J] Oral
｜S (Solid Earth Sciences )
| S-TT Technology & Techniques

Sun. May 26, 2019 3:30 PM - 5:00 PM A07 (TOKYO BAY MAKUHARI HALL)

convener:Shigekazu Kusumoto(Graduate School of Science and Engineering for Research, University of Toyama), Takao Koyama(Earthquake Research Institute, University of Tokyo), Yuji Mitsuhata(AdvancedIndustrial Science and Technology), Shigeo Okuma(Geological Survey of Japan, National Institute of Advanced Industrial Science and Technology (AIST)), Chairperson:Shigekazu Kusumoto, Takao Koyama(東京大学地震研究所火山センター), Shigeo Okuma(産業技術総合研究所), Yuji Mitsuhata(国立研究開発法人　産業技術総合研究所)

Mon. May 27, 2019 3:00 PM - 3:15 PM

[STT46-06] Deep-learning-based Earthquake Detection for Continuous Seismic Network Records

*Keisuke Yano¹, Takahiro Shiina², Sumito Kurata¹, Aitaro Kato², Fumiyasu Komaki¹, Shin'ichi Sakai², Naoshi Hirata² (1.Graduate School of Information Science and Technology, The University of Tokyo, , 2.Earthquake Research Institute, The University of Tokyo)

[S-TT46] Seismic Big Data Analysis Based on the State-of-the-Art of Bayesian Statistics

[J] Oral
｜S (Solid Earth Sciences )
| S-TT Technology & Techniques

Mon. May 27, 2019 1:45 PM - 3:15 PM A08 (TOKYO BAY MAKUHARI HALL)

convener:Hiromichi Nagao(Earthquake Research Institute, The University of Tokyo), Aitaro Kato(Earthquake Research Institute, the University of Tokyo), Takuto Maeda(Graduate School of Science and Technology, Hirosaki University), Keisuke Yano(The university of Tokyo), Chairperson:Nana Yoshimitsu(Earthquake Research Institute, The University of Tokyo), Takeru Matsuda(Graduate School of Information Science and Technology, The University of Tokyo)

Mon. May 27, 2019 12:00 AM - 12:00 AM

[STT46-P01] P-wave Polarity Determination of Waveform Data Observed in Western Japan, Using Deep Learning

*Shota Hara¹, Yukitoshi Fukahata², Yoshihisa Iio² (1.Division of Earth and Planetary Sciences, Graduate School of Science, Kyoto University, 2.Disaster Prevention Research Institute, Kyoto University)

[S-TT46] Seismic Big Data Analysis Based on the State-of-the-Art of Bayesian Statistics

[J] Poster
｜S (Solid Earth Sciences )
| S-TT Technology & Techniques

Mon. May 27, 2019 3:30 PM - 5:00 PM Poster Hall (International Exhibition Hall8, Makuhari Messe)

convener:Hiromichi Nagao(Earthquake Research Institute, The University of Tokyo), Aitaro Kato(Earthquake Research Institute, the University of Tokyo), Takuto Maeda(Graduate School of Science and Technology, Hirosaki University), Keisuke Yano(The university of Tokyo)

Sun. May 26, 2019 9:20 AM - 9:35 AM

[SCG62-02] Automatic Approach to Low-Frequency Earthquakes Detection in Southwest Japan Based on Deep Learning Technique

*Yu Junyu¹, Yuji Yagi¹, Takanori Matsuzawa², Ryo Okuwaki¹ (1.Graduate School of Life and Environmental Sciences,University of Tsukuba, Tsukuba, 2.National Research Institute for Earth Science and Disaster Resilience)

[S-CG62] Potentiality of Machine Learning in Solid Earth Sciences

[J] Oral
｜S (Solid Earth Sciences )
| S-CG Complex & General

Sun. May 26, 2019 9:00 AM - 10:30 AM 304 (3F)

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), Chairperson:Takahiko Uchide(Geological Survey of Japan, AIST), Hirokuni Oda

Presentations by Keyword

Keywords : deep learning

[ACG36-04] Deep-Learning Based Short-Term Prediction Method for Sea Ice Concentration Using Explanatory Variables

[A-CG36] Earth & Environmental Sciences and Artificial Intelligence

[ACG36-05] Remote sensing of cloud using the deep learning based on three-dimensional radiative transfer

[A-CG36] Earth & Environmental Sciences and Artificial Intelligence

[ACG36-07] Time series prediction of cloud cover using whole-sky images and meteorological elements

[A-CG36] Earth & Environmental Sciences and Artificial Intelligence

[ACG36-09] Identification of ships image on SAR data using machine learning

[A-CG36] Earth & Environmental Sciences and Artificial Intelligence

[ACG36-P05] Application of deep learning techniques to precipitation guidance in short-term weather predictions

[A-CG36] Earth & Environmental Sciences and Artificial Intelligence

[SSS04-03] A deep convolutional neural network for localizing and detecting earthquake swarm activity based on full waveforms: Chances, challenges and questions

★Invited Papers

[S-SS04] New methods for seismicity characterization

[STT44-02] Development for upgrading the generalization capability of the seismic damage detection of building based on the deep-learning utilizing aerial photographs

★Invited Papers

[S-TT44] Airborne surveys and monitoring of the Earth

[STT46-06] Deep-learning-based Earthquake Detection for Continuous Seismic Network Records

[S-TT46] Seismic Big Data Analysis Based on the State-of-the-Art of Bayesian Statistics

[STT46-P01] P-wave Polarity Determination of Waveform Data Observed in Western Japan, Using Deep Learning

[S-TT46] Seismic Big Data Analysis Based on the State-of-the-Art of Bayesian Statistics

[SCG62-02] Automatic Approach to Low-Frequency Earthquakes Detection in Southwest Japan Based on Deep Learning Technique

[S-CG62] Potentiality of Machine Learning in Solid Earth Sciences