Dilated-RNNs: A Deep Approach for Continuous Volcano-Seismic Events Recognition-Reference-Cited by-同舟云学术

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Dilated-RNNs: A Deep Approach for Continuous Volcano-Seismic Events Recognition

Published:2024 Issue: Volume:17 Page:11857-11865
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Titos Manuel¹^ORCID,Carthy Joe¹,García Luz¹^ORCID,Barnie Talfan²,Benítez Carmen¹^ORCID

Affiliation:

1. Department of Signal Theory, Telematics and Communications, and the Center for Information and Communication Technologies Research (CITIC), University of Granada, Granada, Spain

2. Processing and Research Division, Icelandic Meteorological Office, Reykjavík, Iceland

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/4609443/10330207/10582421.pdf?arnumber=10582421

Reference50 articles.

1. Continuous automatic classification of seismic signals of volcanic origin at Mt. Merapi, Java, Indonesia;Ohrnberger,2001

2. A Review of Machine Learning and Deep Learning Applications

3. The new science of volcanoes harnesses AI, satellites and gas sensors to forecast eruptions

4. How AI and satellites could help predict volcanic eruptions

5. Deep learning

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