Performance enhancement of deep neural network using fusional data assimilation and divide-and-conquer approach; case study: earthquake magnitude calculation

R Esmaeili, R Kimiaefar, A Hajian… - Neural Computing and …, 2024 - Springer
The presence of" ill-posed samples" specifically in low-volume datasets leads to accuracy
decrement in the learning procedure and the generalization of neural networks. Such …

Foundation Models for Geophysics: Reviews and Perspectives

Q Liu, J Ma - arXiv preprint arXiv:2406.03163, 2024 - arxiv.org
Recently, large models, or foundation models have demonstrated outstanding performance
and have been applied in a variety of disciplines, such as chemistry, biology, economics …

ICAT-net: a lightweight neural network with optimized coordinate attention and transformer mechanisms for earthquake detection and phase picking

XN Li, FJ Chen, YP Lai, P Tang, XJ Liang - The Journal of …, 2025 - Springer
Seismic signal detection is a crucial technology for enhancing the efficiency of earthquake
early warning systems. However, existing deep learning-based seismic signal detection …

PAW: A Deep Learning Model for Predicting Amplitude Windows in Seismic Signals

AM Villegas Suarez, D Reiter, J Rolfs… - 2024 IEEE 11th …, 2024 - ieeexplore.ieee.org
Subsurface earthquakes and explosions generate seismic wavefields that are recorded as
time-domain signals on sensor networks around the world. To compute key characteristics …

ICAT-net: Integration of Coordinate Attention and Transformer network for seismic signal detection and phase arrival picking

XN Li, F Chen, YP Lai, P Tang, XJ Liang - 2024 - researchsquare.com
Seismic signal detection is a crucial technology for enhancing the efficiency of earthquake
early warning systems. However, existing deep learning-based seismic signal detection …