Results 101 to 110 of about 4,442 (191)

High Resolution Seismic Waveform Generation Using Denoising Diffusion

Journal of Geophysical Research: Machine Learning and Computation
Abstract Accurate prediction and synthesis of seismic waveforms are crucial for seismic‐hazard assessment and earthquake‐resistant infrastructure design. Existing prediction methods, such as ground‐motion models and physics‐based wavefield simulations, often fail to capture the full complexity of seismic ...
Kadek Hendrawan Palgunadi, Andreas Bergmeister, Andrea Bosisio, Laura A. Ermert, Maria Koroni, Nathanaël Perraudin, Simon Dirmeier, Men‐Andrin Meier   +7 more
openaire   +2 more sources

End-to-end seismic signals denoising via deep residual convolution and self-attention mechanisms

大数据
Denoising of seismic waveform signals is crucial for seismic monitoring and seismological research. To this end, we propose an end-to-end deep learning method for denoising seismic waveforms.
Zhao Botao, Kang Zuheng, He Yayun, Peng Junqing, Zhang Xulong, Qu Xiaoyang, Tan Yipei, Chen Yule, Xiao Chunguang, Wang Jianzong   +9 more
doaj  

Efficient seismic data denoising via multi-scale attention network with depthwise separable and residual dilated convolutions. [PDF]

Sci Rep
Yao Z, Hao L, Qin L, Chen J, Li W.
europepmc   +1 more source

Directional adaptive mode total variation for seismic data denoising. [PDF]

Sci Rep
Banjade TP, Zhou C, Yang Y, Li H, Deng J.   +4 more
europepmc   +1 more source

Model-Driven Processing of Passive Seismic While Drilling Data Acquired Using Distributed Acoustic Sensing Without Conventional Drill-Bit Pilot Measurements. [PDF]

Sensors (Basel)
Al-Hemyari E, Pevzner R, Tertyshnikov K.
europepmc   +1 more source

Seismic random noise separation and suppression based on improved variational mode decomposition via grey wolf optimization. [PDF]

PLoS One
Yao Z, Li W, Zhu J, Hao L, Xing M.
europepmc   +1 more source

Improved first arrival picking of microseismic P-waves in coal mines using multi-denoising and adaptive characteristic functions. [PDF]

Sci Rep
Zhang Y, Zhan K, Song P, Liang C, Xu R, Kong C.   +5 more
europepmc   +1 more source

Hybrid multi-resolution network for DAS data denoising. [PDF]

PLoS One
Ding L, Sun H, Chen H, Hu X.
europepmc   +1 more source

Deep Learning-Based Denoising of Noisy Vibration Signals from Wavefront Sensors Using BiL-DCAE. [PDF]

Sensors (Basel)
Pan Y, Luo Q, Fan Y, Chen H, Zhou D, Luo H, Jiang W, Su J.   +7 more
europepmc   +1 more source

Test-Time Augmentations and Quality Controls for Improving Regional Seismic Phase Picking. [PDF]

Sensors (Basel)
Han B, Tang L, Ma L, Kong H, Xiao Z.
europepmc   +1 more source