Explainable time-frequency convolutional neural network for microseismic waveform classification

DOI10.1016/J.INS.2020.08.109zbMath1475.86002OpenAlexW3083046978MaRDI QIDQ2055569

Yanyan Li

Publication date: 1 December 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2020.08.109

zbMATH Keywords

explainable convolutional neural networkmicroseismic waveformtime-series classification

Mathematics Subject Classification ID

Soil and rock mechanics (74L10) Seismology (including tsunami modeling), earthquakes (86A15) Computational methods for problems pertaining to geophysics (86-08)

Uses Software

• Grad-CAM
• DBA

Cites Work

• A practical guide to splines
• Time series classification with ensembles of elastic distance measures
• Convolutional neural network learning for generic data classification
• Interpretable regularized class association rules algorithm for classification in a categorical data space
• Early classification of time series using multi-objective optimization techniques
• Knowledge extraction from deep convolutional neural networks applied to cyclo-stationary time-series classification
• Neural networks and physical systems with emergent collective computational abilities.

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