The CGAS Deep Learning Algorithm for P-Wave Arrival Time Picking of Mining Microseismic Events
Author:
Affiliation:
1. College of Information, Liaoning University, Shenyang, China
2. School of Mechanics and Engineering, Liaoning Technical University, Fuxin, China
Funder
National Natural Science Foundation of China
Education Department of Liaoning Province Science and Technology Research
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10255552.pdf?arnumber=10255552
Reference40 articles.
1. Enhancing Seismic P-Wave Arrival Picking by Target-Oriented Detection of the Local Windows Using Faster-RCNN
2. Deep learning for P-wave arrival picking in earthquake early warning
3. Identification of Seismic Wave First Arrivals from Earthquake Records via Deep Learning
4. Research on first-arrival picking of seismic P-wave based on U-Net++;liu;Journal of Taiyuan University of Technology,2023
5. Microearthquakes at Flathead Lake, Montana: A study using automatic earthquake processing
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1. PSSegNet: Segmenting the P- and S-Phases in Microseismic Signals through Deep Learning;Mathematics;2023-12-30
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