Bueno, A, Zuccarello, L, Díaz-Moreno, A, Woollam, J, Titos, M, Benítez, C, Álvarez, I, Prudencio, J and De Angelis, S 
ORCID: 0000-0003-2636-3056
(2020)
PICOSS: Python Interface for the Classification of Seismic Signals.
Computers & Geosciences, 142.
p. 104531.
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PICOSS_vfinal_.pdf - Author Accepted Manuscript Download (3MB) | Preview |
Abstract
Over the last decade machine learning has become increasingly popular for the analysis and characterization of volcano-seismic data. One of the requirements for the application of machine learning methods to the problem of classifying seismic time series is the availability of a training dataset; that is a suite of reference signals, with known classification used for initial validation of the machine outcome. Here, we present PICOSS (Python Interface for the Classification of Seismic Signals), a modular data-curator platform for volcano-seismic data analysis, including detection, segmentation and classification. PICOSS has exportability and standardization at its core; users can select automatic or manual workflows to select and label seismic data from a comprehensive suite of tools, including deep neural networks. The modular implementation of PICOSS includes a portable and intuitive graphical user interface to facilitate essential data labelling tasks for large-scale volcano seismic studies.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Volcanoes, Software, Classification, segmentation, Detection |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 16 Sep 2020 08:45 |
| Last Modified: | 18 Jan 2023 23:33 |
| DOI: | 10.1016/j.cageo.2020.104531 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3101391 |
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