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Found 5 papers, 2 papers with code
SeisCLIP: A seismology foundation model pre-trained by multi-modal data for multi-purpose seismic feature extraction
Training specific deep learning models for particular tasks is common across various domains within seismology.
Multi-task multi-station earthquake monitoring: An all-in-one seismic Phase picking, Location, and Association Network (PLAN)
Overall, our study provides for the first time a prototype self-consistent all-in-one system of simultaneous seismic phase picking, association, and location, which has the potential for next-generation autonomous earthquake monitoring.
A Deep-Learning-Based Neural Decoding Framework for Emotional Brain-Computer Interfaces
Reading emotions precisely from segments of neural activity is crucial for the development of emotional brain-computer interfaces.
Deep learning based sferics recognition for AMT data processing in the dead band
The subsequent processing results show that our method can significantly improve S/N and effectively solve the problem of lack of energy in dead band.
Convolutional Neural Network with Median Layers for Denoising Salt-and-Pepper Contaminations
We propose a deep fully convolutional neural network with a new type of layer, named median layer, to restore images contaminated by the salt-and-pepper (s&p) noise.
