Discriminating seismic events using 1D and 2D CNNs : applications to volcanic and tectonic datasets

• 資料種別: 記事
• タイトル: Discriminating seismic events using 1D and 2D CNNs : applications to volcanic and tectonic datasets
• 著者・編者: Masaru Nakano; Daisuke Sugiyama
• 出版事項: 日本 : The Society of Geomagnetism and Earth, Planetary and Space Sciences
• 出版年月日等: 2022-09-08
• 出版年（W3CDTF）: 2022-09-08
• タイトル（掲載誌）: EPS : Earth, Planets and Space
• 巻号年月日等（掲載誌）: 74(134)
• 掲載巻: 74(134)
• ISSN（掲載誌）: 1880-5981
• ISSN-L（掲載誌）: 1343-8832
• 本文の言語コード: eng
• DOI: 10.1186/s40623-022-01696-1; https://doi.org/10.1186/s40623-022-01696-1
• 国立国会図書館永続的識別子: info:ndljp/pid/12685421; https://dl.ndl.go.jp/pid/12685421
• コレクション（共通）: 障害者向け資料
• コレクション（障害者向け資料：レベル1）: テキストデータ
• コレクション（個別）: 国立国会図書館デジタルコレクション > 電子書籍・電子雑誌 > その他; https://dl.ndl.go.jp/collections/B00035
• 収集根拠: オンライン資料収集制度
• 受理日（W3CDTF）: 2023-03-07T16:17:02+09:00
• 保存日（W3CDTF）: 2023-03-07
• 記録形式（IMT）: application/pdf
• オンライン閲覧公開範囲: 国立国会図書館内限定公開
• デジタル化資料送信: 図書館・個人送信対象外
• 遠隔複写可否（NDL）: 可
• 掲載誌（URI）: https://earth-planets-space.springeropen.com/articles
• 掲載誌（国立国会図書館永続的識別子）: info:ndljp/pid/12287068; https://dl.ndl.go.jp/pid/12287068
• 連携機関・データベース: 国立国会図書館 : 国立国会図書館デジタルコレクション; https://dl.ndl.go.jp

• 要約等: コレクション : 国立国会図書館デジタルコレクション > 電子書籍・電子雑誌 > その他
• DOI: 10.1186/s40623-022-01696-1; https://doi.org/10.1186/s40623-022-01696-1; 10.21203/rs.3.rs-1829830/v1; https://doi.org/10.21203/rs.3.rs-1829830/v1
• オンライン閲覧公開範囲: インターネット公開
• 関連情報（URI）: http://id.ndl.go.jp/digimeta/12685421; https://dl.ndl.go.jp/pid/12685421; https://link.springer.com/content/pdf/10.1186/s40623-022-01696-1.pdf; https://link.springer.com/article/10.1186/s40623-022-01696-1/fulltext.html
• 参照: Recent advances in earthquake seismology using machine learning; https://cir.nii.ac.jp/crid/1360865815689043456
• 参照: Tidal Response in Shallow Tectonic Tremors; https://cir.nii.ac.jp/crid/1360004229807854720; Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking; https://cir.nii.ac.jp/crid/1360017290175836032; New, improved version of generic mapping tools released; https://cir.nii.ac.jp/crid/1360292617909532032; Nonvolcanic Deep Tremor Associated with Subduction in Southwest Japan; https://cir.nii.ac.jp/crid/1360292617909770624; Development and application of an advanced ocean floor network system for megathrust earthquakes and tsunamis; https://cir.nii.ac.jp/crid/1360292617915981056; Earthquake detection through computationally efficient similarity search; https://cir.nii.ac.jp/crid/1360292619203709696; CRED: A Deep Residual Network of Convolutional and Recurrent Units for Earthquake Signal Detection; https://cir.nii.ac.jp/crid/1360574093942121088; <i>P</i> Wave Arrival Picking and First‐Motion Polarity Determination With Deep Learning; https://cir.nii.ac.jp/crid/1360574094261251200; Geophysical Exploration Linking Deep Earth and Backyard Geology; https://cir.nii.ac.jp/crid/1360580234812342272; Shallow very-low-frequency earthquakes accompany slow slip events in the Nankai subduction zone; https://cir.nii.ac.jp/crid/1360846641753424128; Construction of the DONET real-time seafloor observatory for earthquakes and tsunami monitoring; https://cir.nii.ac.jp/crid/1360855567868597504; Artificial neural network-based seismic detector; https://cir.nii.ac.jp/crid/1360857613593548416; In-depth comparison of deep artificial neural network architectures on seismic events classification; https://cir.nii.ac.jp/crid/1360861711150273664; DeepPhasePick: A method for detecting and picking seismic phases from local earthquakes based on highly optimized convolutional and recurrent deep neural networks; https://cir.nii.ac.jp/crid/1360861711921349760; Probing Slow Earthquakes With Deep Learning; https://cir.nii.ac.jp/crid/1360861712140395520; Discrimination of Earthquakes and Underwater Explosions Using Neural Networks; https://cir.nii.ac.jp/crid/1361137045856822400; Machine learning reveals cyclic changes in seismic source spectra in Geysers geothermal field; https://cir.nii.ac.jp/crid/1361137046322243712; Discrimination of Seismic Signals from Earthquakes and Tectonic Tremor by Applying a Convolutional Neural Network to Running Spectral Images; https://cir.nii.ac.jp/crid/1361413117941286400; Automatic Classification of Seismic Signals at Mt. Vesuvius Volcano, Italy, Using Neural Networks; https://cir.nii.ac.jp/crid/1361699993642263424; Detecting tectonic tremor through frequency scanning at a single station: Application to the Cascadia margin; https://cir.nii.ac.jp/crid/1361699993948107392; Seismic Event and Phase Detection Using Time–Frequency Representation and Convolutional Neural Networks; https://cir.nii.ac.jp/crid/1361699994197630848; Generalized Seismic Phase Detection with Deep Learning; https://cir.nii.ac.jp/crid/1362825893263312768; Long-period volcano seismicity: its source and use in eruption forecasting; https://cir.nii.ac.jp/crid/1363388846310243712; MyShake: A smartphone seismic network for earthquake early warning and beyond; https://cir.nii.ac.jp/crid/1363670319145977856; Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position; https://cir.nii.ac.jp/crid/1363670321239371008; Deep learning; https://cir.nii.ac.jp/crid/1363951794115240960; Convolutional neural network for earthquake detection and location; https://cir.nii.ac.jp/crid/1363951794885739648; Slow Earthquakes Coincident with Episodic Tremors and Slow Slip Events; https://cir.nii.ac.jp/crid/1364233269991901952; NIED MOWLAS (Monitoring of Waves on Land and Seafloor); https://cir.nii.ac.jp/crid/1460002330936432384; Application of deep learning-based neural networks using theoretical seismograms as training data for locating earthquakes in the Hakone volcanic region, Japan; https://cir.nii.ac.jp/crid/2050307417127739136; MOWLAS : NIED observation network for earthquake, tsunami and volcano; https://cir.nii.ac.jp/crid/2050870367075037952; A convolutional neural network-based classification of local earthquakes and tectonic tremors in Sanriku-oki, Japan, using S-net data; https://cir.nii.ac.jp/crid/2051151842060077440
• 連携機関・データベース: 国立情報学研究所 : CiNii Research; https://cir.nii.ac.jp/
• 提供元機関・データベース: 雑誌記事索引データベース; https://ndlsearch.ndl.go.jp; Crossref; https://www.crossref.org; 科学研究費助成事業データベース; https://kaken.nii.ac.jp/ja
• 書誌ID（NDLBibID）: 12685421; http://id.ndl.go.jp/bib/12685421