Tensor-Based Learning Framework for Automatic Multichannel Volcano-Seismic Classification

Tensor-Based Learning Framework for Automatic Multichannel Volcano-Seismic Classification

This article proposes a supervised tensor-based learning framework for classifying volcano-seismic events from signals recorded at the Ubinas volcano, in Peru, during a period of great activity in 2009. The proposed method is fully tensorial, as it integrates the three main steps of the automatic cl...

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Bibliographic Details
Main Authors: Antonio Augusto Teixeira Peixoto, Carlos Alexandre Rolim Fernandes, Pablo Eduardo Espinoza Lara, Adolfo Inza, Jerome I Mars, Jean-Philippe Metaxian, Mauro Dalla Mura, Marielle Malfante
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Classification
machine learning (ML)
multidimensional signal processing
tensor learning
volcano
volcano-seismic signals
Online Access:https://ieeexplore.ieee.org/document/9408367/

Internet

https://ieeexplore.ieee.org/document/9408367/

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