DASFormer: self-supervised pretraining for earthquake monitoring
Abstract Earthquake monitoring is a fundamental task to unravel the underlying physics of earthquakes and mitigate associated hazards for public safety. Distributed acoustic sensing, or DAS, which transforms pre-existing telecommunication cables into ultra-dense seismic networks, offers a cost-effec...
Saved in:
| Main Authors: | Qianggang Ding, Zhichao Shen, Weiqiang Zhu, Bang Liu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-07-01
|
| Series: | Visual Intelligence |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44267-025-00085-y |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Physics-Guided Self-Supervised Learning Full Waveform Inversion with Pretraining on Simultaneous Source
by: Qiqi Zheng, et al.
Published: (2025-06-01) -
A Pretrained Spatio-Temporal Hypergraph Transformer for Multi-Stock Trend Forecasting
by: Yuchen Wu, et al.
Published: (2025-05-01) -
SHAZAM: Self-Supervised Change Monitoring for Hazard Detection and Mapping
by: Samuel Garske, et al.
Published: (2025-01-01) -
EARTHQUAKE OF 27 AUGUST 2008 IN THE SOUTHERN BAIKAL AREA AND ITS PRECURSORS
by: Rudolf M. Semenov
Published: (2015-09-01) -
COVID-19 Data Analysis: The Impact of Missing Data Imputation on Supervised Learning Model Performance
by: Jorge Daniel Mello-Román, et al.
Published: (2025-03-01)