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図書

Detection of deep low-frequency tremors from continuous paper records at a station in southwest Japan about 50 years ago based on convolutional neural network for seismogram images (Mathematical engineering technical reports ; METR 2022-6)

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Detection of deep low-frequency tremors from continuous paper records at a station in southwest Japan about 50 years ago based on convolutional neural network for seismogram images

(Mathematical engineering technical reports ; METR 2022-6)

Call No. (NDL)
M19-D225
Bibliographic ID of National Diet Library
032930966
Material type
図書
Author
Ryosuke Kaneko, Hiromichi Nagao, Shin-ichi Ito, Hiroshi Tsuruoka and Kazushige Obara [著]
Publisher
Department of Mathematical Informatics, Graduate School of Information Science and Technology, the University of Tokyo
Publication date
2022.5
Material Format
Paper
Capacity, size, etc.
24 p ; 30 cm
NDC
-
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Paper

Material Type
図書
Title
Detection of deep low-frequency tremors from continuous paper records at a station in southwest Japan about 50 years ago based on convolutional neural network for seismogram images
Title Transcription
Detection of deep low-frequency tremors from continuous paper records at a station in southwest Japan about 50 years ago based on convolutional neural network for seismogram images
Author/Editor
Ryosuke Kaneko, Hiromichi Nagao, Shin-ichi Ito, Hiroshi Tsuruoka and Kazushige Obara [著]
Series Title
Mathematical engineering technical reports ; METR 2022-6
Publication, Distribution, etc.
Tokyo : Department of Mathematical Informatics, Graduate School of Information Science and Technology, the University of Tokyo (出版)
Publication Date
2022.5
Publication Date (W3CDTF)
2022
Extent
24 p
Size
30 cm