Results 11 to 20 of about 3,178,879 (308)
Earthquake Detection with tinyML
Seismological Research Letters, 2023 Earthquake detection is the critical first step in earthquake early warning (EEW) systems. For robust EEW systems, detection accuracy, detection latency, and sensor density are critical to providing real-time earthquake alerts.
Timothy Clements, Clements, Timothy
core +4 more sources
Earthquake Damage Detection Using Before and After Earthquake Satellite Images
2018 IEEE International Conference on Electro/Information Technology (EIT), 2018 After experiencing many earthquakes all around the world, earthquake damage assessment has attracted a great deal of attention from both researchers and practitioners.
Kasim A. Korkmaz +3 more
core +3 more sources
Convolutional neural network for earthquake detection and location. [PDF]
Sci Adv, 2018 ConvNetQuake is the first neural network for detection and location of earthquakes from seismograms.
Perol T, Gharbi M, Denolle M.
europepmc +7 more sources
Bayesian Detection of Streamflow Response to Earthquakes [PDF]
Water Resources Research, 2021 AbstractDetecting whether and how river discharge responds to strong earthquake shaking can be time‐consuming and prone to operator bias when checking hydrographs from hundreds of gauging stations. We use Bayesian piecewise regression models to show that up to a fifth of all gauging stations across Chile had their largest change in daily streamflow ...
Oliver Korup +2 more
openaire +2 more sources
Detecting Real Earthquakes Using Artificial Earthquakes: On the Use of Synthetic Waveforms in Matched‐Filter Earthquake Detection [PDF]
Geophysical Research Letters, 2018 Abstract Matched‐filters are an increasingly popular tool for earthquake detection, but their reliance on a priori knowledge of the targets of interest limits their application to regions with previously documented seismicity. We explore an extension to the matched‐filter method to detect earthquakes and low‐frequency earthquakes on ...
John Townend, Calum Chamberlain
openaire +3 more sources
Most complicated lock pattern-based seismological signal framework for automated earthquake detection [PDF]
, 2023 Background: Seismic signals record earthquakes and also noise from different sources. The influence of noise makes it difficult to interpret seismograph signals correctly.
Baygin, M +29 more
core +1 more source
Earthquake Detection at the Edge: IoT Crowdsensing Network
Information, 2022 State-of-the-art Earthquake Early Warning systems rely on a network of sensors connected to a fusion center in a client–server paradigm. The fusion center runs different algorithms on the whole data set to detect earthquakes. Instead, we propose moving computation to the edge, with detector nodes that probe the environment and process information from ...
Bassetti, Enrico, Panizzi, Emanuele
openaire +3 more sources
Shapelets for earthquake detection
CoRR, 2019 This paper introduces EQShapelets (EarthQuake Shapelets) a time-series shape-based approach embedded in machine learning to autonomously detect earthquakes. It promises to overcome the challenges in the field of seismology related to automated detection and cataloging of earthquakes.
Monica Arul, Ahsan Kareem
openaire +3 more sources
Frontiers in Earth Science, 2023 In response to the challenge of improving the performance of deep learning models for earthquake detection in low signal-to-noise ratio environments, this article introduces a new earthquake detection model called ECPickNet.
Shuwang Wang +6 more
doaj +1 more source
Earthquake source parameters of the 2009 Mw 7.8 Fiordland (New Zealand) earthquake from L-band InSAR observations [PDF]
, 2011 The 2009 MW7.8 Fiordland (New Zealand) earthquake is the largest to have occurred in New Zealand since the 1931 Mw 7.8 Hawke’s Bay earthquake, 1 000 km to the northwest.
Qu, W. +7 more
core +1 more source