Cover Image

Fully Data-Driven Model for Increasing Sampling Rate Frequency of Seismic Data using Super-Resolution Generative Adversarial Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gholizadeh, Navid, Katebi, Javad
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Signal Processing Geophysics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

An Empirical Study of Large-Scale Data-Driven Full Waveform Inversion
by: Jin, Peng, et al.
Published: (2023)

Evaluating PhaseNet on Teleseismic Data with MsPASS
by: Ma, Jinxin, et al.
Published: (2026)

High-Rate Phase Association with Travel Time Neural Fields
by: Shi, Cheng, et al.
Published: (2023)

GAN-supervised Seismic Data Reconstruction: An Enhanced-Learning for Improved Generalization
by: Goyes-Penafiel, Paul, et al.
Published: (2023)

Seismic First Break Picking in a Higher Dimension Using Deep Graph Learning
by: Wang, Hongtao, et al.
Published: (2024)

A CNN-BiLSTM Model with Attention Mechanism for Earthquake Prediction
by: Kavianpour, Parisa, et al.
Published: (2021)

Global Seismic Monitoring using Operational Subsea Cable
by: Mazur, Mikael, et al.
Published: (2024)

Automatic Differentiation-based Full Waveform Inversion with Flexible Workflows
by: Liu, Feng, et al.
Published: (2024)

Fast ground penetrating radar dual-parameter full waveform inversion method accelerated by hybrid compilation of CUDA kernel function and PyTorch
by: Liu, Lei, et al.
Published: (2025)

FiLark: a streaming-first software framework for end-to-end exploration, annotation, and algorithm integration in distributed acoustic sensing
by: Li, Jintao, et al.
Published: (2026)

Auto-Linear Phenomenon in Subsurface Imaging
by: Feng, Yinan, et al.
Published: (2023)

Joint Microseismic Event Detection and Location with a Detection Transformer
by: Yang, Yuanyuan, et al.
Published: (2023)

Enhancing Deep Learning based RMT Data Inversion using Gaussian Random Field
by: Ghosal, Koustav, et al.
Published: (2024)

Denoising of Geodetic Time Series Using Spatiotemporal Graph Neural Networks: Application to Slow Slip Event Extraction
by: Costantino, Giuseppe, et al.
Published: (2024)

Leveraging Time-Series Foundation Model for Subsurface Well Logs Prediction and Anomaly Detection
by: Koeshidayatullah, Ardiansyah, et al.
Published: (2024)

DASPack: Controlled Data Compression for Distributed Acoustic Sensing
by: Segui, Aleix, et al.
Published: (2025)

Forecasting Ionospheric Irregularities on GNSS Lines of Sight Using Dynamic Graphs with Ephemeris Conditioning
by: Turkmen, Mert Can, et al.
Published: (2026)

Self-Supervised Temporal Super-Resolution of Energy Data using Generative Adversarial Transformer
by: Mu, Xuanhao, et al.
Published: (2025)

High-Resolution Trans-Oceanic Distributed Acoustic Sensing Enabled by a Bi-Directional Sensor Implementation
by: Mazur, Mikael, et al.
Published: (2026)

WISE: full-Waveform variational Inference via Subsurface Extensions
by: Yin, Ziyi, et al.
Published: (2023)

Data-Driven and Theory-Guided Pseudo-Spectral Seismic Imaging Using Deep Neural Network Architectures
by: Zerafa, Christopher
Published: (2025)

Training a Distributed Acoustic Sensing Traffic Monitoring Network With Video Inputs
by: Cohen, Khen, et al.
Published: (2024)

Multimodal Atmospheric Super-Resolution With Deep Generative Models
by: Chakraborty, Dibyajyoti, et al.
Published: (2025)

Modeling measurements for quantitative imaging subsurface targets
by: Kim, Arnold, et al.
Published: (2025)

Self-Updating Vehicle Monitoring Framework Employing Distributed Acoustic Sensing towards Real-World Settings
by: Wang, Xi, et al.
Published: (2024)

Restoring Super-High Resolution GPS Mobility Data
by: Yonekura, Haruki, et al.
Published: (2024)

Ground-roll Separation From Land Seismic Records Based on Convolutional Neural Network
by: Jia, Zhuang, et al.
Published: (2024)

High Resolution Seismic Waveform Generation using Denoising Diffusion
by: Palgunadi, Kadek Hendrawan, et al.
Published: (2024)

Direct Estimation of Porosity from Seismic Data using Rock and Wave Physics Informed Neural Networks (RW-PINN)
by: Vashisth, Divakar, et al.
Published: (2022)

A Physics-guided Generative AI Toolkit for Geophysical Monitoring
by: Yang, Junhuan, et al.
Published: (2024)

Effective Data Selection for Seismic Interpretation through Disagreement
by: Benkert, Ryan, et al.
Published: (2024)

Enhanced Geological Prediction for Tunnel Excavation Using Full Waveform Inversion Integrating Sobolev Space Regularization with a Quadratic Penalty Method
by: Li, Jiahang, et al.
Published: (2024)

WAFER: A new method to retrieve sun-induced fluorescence based on spectral wavelet decompositions
by: Oehl, Veronika, et al.
Published: (2025)

Data-Driven Dynamic Friction Models based on Recurrent Neural Networks
by: Cortes, Gaëtan, et al.
Published: (2024)

Seismic Data Interpolation via Denoising Diffusion Implicit Models with Coherence-corrected Resampling
by: Wei, Xiaoli, et al.
Published: (2023)

Transcending Classical Neural Network Boundaries: A Quantum-Classical Synergistic Paradigm for Seismic Data Processing
by: Yuan, Zhengyi, et al.
Published: (2026)

SeisRDT: Latent Diffusion Model Based On Representation Learning For Seismic Data Interpolation And Reconstruction
by: Wang, Shuang, et al.
Published: (2025)

SeisFusion: Constrained Diffusion Model with Input Guidance for 3D Seismic Data Interpolation and Reconstruction
by: Wang, Shuang, et al.
Published: (2024)

RF Challenge: The Data-Driven Radio Frequency Signal Separation Challenge
by: Lancho, Alejandro, et al.
Published: (2024)

Enhancing Activity Recognition After Stroke: Generative Adversarial Networks for Kinematic Data Augmentation
by: Hadley, Aaron J., et al.
Published: (2024)