Classifying space-time images obtained from distributed acoustic sensing
Classifying space-time images obtained from distributed acoustic sensing
In this paper we present a classifier that was trained on space-time images obtained from distributed acoustic sensing, for the purpose of monitoring earthquakes. The model is capable of discriminating between actual and non-earthquake events.
Matthaiou, Ioannis
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Masoudi, Ali
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Araki, Eiichiro
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Kodaira, Shuichi
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Modafferi, Stefano
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Brambilla, Gilberto
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31 July 2023
Matthaiou, Ioannis
7855a890-8929-4c90-a08c-9672fd7f6fda
Masoudi, Ali
8073fb9b-2e6c-46c9-89cf-cb8670d76dc0
Araki, Eiichiro
48fe1389-0977-456f-bc3e-5ba2f3a96d02
Kodaira, Shuichi
98fd4032-ee7d-43a9-b90d-438d3b60d24c
Modafferi, Stefano
2f15a6fa-a4c3-4f43-998f-df7d88f08a78
Brambilla, Gilberto
815d9712-62c7-47d1-8860-9451a363a6c8
Matthaiou, Ioannis, Masoudi, Ali, Araki, Eiichiro, Kodaira, Shuichi, Modafferi, Stefano and Brambilla, Gilberto
(2023)
Classifying space-time images obtained from distributed acoustic sensing.
Optica Sensing Congress, , Munich, Germany.
31 Jul - 04 Aug 2023.
Record type:
Conference or Workshop Item
(Paper)
Abstract
In this paper we present a classifier that was trained on space-time images obtained from distributed acoustic sensing, for the purpose of monitoring earthquakes. The model is capable of discriminating between actual and non-earthquake events.
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Published date: 31 July 2023
Venue - Dates:
Optica Sensing Congress, , Munich, Germany, 2023-07-31 - 2023-08-04
Identifiers
Local EPrints ID: 481808
URI: http://eprints.soton.ac.uk/id/eprint/481808
PURE UUID: fbf1a91f-6325-4089-842b-d0c3cf66cd4e
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Date deposited: 08 Sep 2023 16:41
Last modified: 28 Oct 2023 02:34
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Contributors
Author:
Eiichiro Araki
Author:
Shuichi Kodaira
Author:
Stefano Modafferi
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