Recent advances in earthquake seismology using machine learning
Given the recent developments in machine-learning technology, its application has rapidly
progressed in various fields of earthquake seismology, achieving great success. Here, we …
progressed in various fields of earthquake seismology, achieving great success. Here, we …
[HTML][HTML] INSTANCE–the Italian seismic dataset for machine learning
The Italian earthquake waveform data are collected here in a dataset suited for machine
learning analysis (ML) applications. The dataset consists of nearly 1.2 million three …
learning analysis (ML) applications. The dataset consists of nearly 1.2 million three …
High-precision microseismic source localization using a fusion network combining convolutional neural network and transformer
Q Feng, L Han, L Ma, Q Li - Surveys in Geophysics, 2024 - Springer
Microseismic source localization methods with deep learning can directly predict the source
location from recorded microseismic data, showing remarkably high accuracy and efficiency …
location from recorded microseismic data, showing remarkably high accuracy and efficiency …
Robust feature extraction for geochemical anomaly recognition using a stacked convolutional denoising autoencoder
Y **
Landslide susceptibility map** (LSM) is critical for risk assessment and mitigation.
Generalization ability and prediction uncertainty are the current challenges for LSM but have …
Generalization ability and prediction uncertainty are the current challenges for LSM but have …
[HTML][HTML] GeoINR 1.0: an implicit neural network approach to three-dimensional geological modelling
Implicit neural representation (INR) networks are emerging as a powerful framework for
learning three-dimensional shape representations of complex objects. These networks can …
learning three-dimensional shape representations of complex objects. These networks can …
Development of a high-performance seismic phase picker using deep learning in the Hakone volcanic area
A Kim, Y Nakamura, Y Yukutake, H Uematsu… - Earth, Planets and …, 2023 - Springer
In volcanic regions, active earthquake swarms often occur in association with volcanic
activity, and their rapid detection and analysis are crucial for volcano disaster prevention …
activity, and their rapid detection and analysis are crucial for volcano disaster prevention …
A systematic review of Earthquake Early Warning (EEW) systems based on Artificial Intelligence
Abstract Early Earthquake Warning (EEW) systems alarm about ongoing earthquakes to
reduce their devastating human and financial damages. In complicated tasks like …
reduce their devastating human and financial damages. In complicated tasks like …
Deep convolutional autoencoders as generic feature extractors in seismological applications
The idea of using a deep autoencoder to encode seismic waveform features and then use
them in different seismological applications is appealing. In this paper, we designed tests to …
them in different seismological applications is appealing. In this paper, we designed tests to …
Discriminating seismic events using 1D and 2D CNNs: applications to volcanic and tectonic datasets
M Nakano, D Sugiyama - Earth, Planets and Space, 2022 - Springer
Detecting seismic events, discriminating between different event types, and picking P-and S-
wave arrival times are fundamental but laborious tasks in seismology. In response to the …
wave arrival times are fundamental but laborious tasks in seismology. In response to the …