Junxing Cao

According to our database1, Junxing Cao authored at least 14 papers between 2008 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2023
Explainable Convolutional Neural Networks Driven Knowledge Mining for Seismic Facies Classification.
IEEE Trans. Geosci. Remote. Sens., 2023

Deep Neural Networks for Direct Hydrocarbon Detection in Prestack Seismic Data Based on AVO Analysis.
IEEE Trans. Geosci. Remote. Sens., 2023

Seismic Impedance Inversion Using a Joint Deep Learning Model Based on Convolutional Neural Network and Transformer.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023

A Lithology Identification Approach Using Well Logs Data and Convolutional Long Short-Term Memory Networks.
IEEE Geosci. Remote. Sens. Lett., 2023

2022
Deblending for Hybrid Simultaneous-Source Data.
IEEE Trans. Geosci. Remote. Sens., 2022

End-to-End Deblending of Simultaneous Source Data Using Transformer.
IEEE Geosci. Remote. Sens. Lett., 2022

Spatiotemporal Synergistic Ensemble Deep Learning Method and Its Application to S-Wave Velocity Prediction.
IEEE Geosci. Remote. Sens. Lett., 2022

A Hierarchical Clustering Method of SOM Based on DTW Distance for Variable-Length Seismic Waveform.
IEEE Geosci. Remote. Sens. Lett., 2022

Horizon Picking Using Two-Branch Network With Spatial and Time-Frequency Features.
IEEE Geosci. Remote. Sens. Lett., 2022

AVO Analysis Combined With Teager-Kaiser Energy Methods for Hydrocarbon Detection.
IEEE Geosci. Remote. Sens. Lett., 2022

2021
Detecting and Analyzing the Displacement of a Small-Magnitude Earthquake Cluster in Rong County, China by the GACOS Based InSAR Technology.
Remote. Sens., 2021

Visualization Analysis of Seismic Facies Based on Deep Embedded SOM.
IEEE Geosci. Remote. Sens. Lett., 2021

2020
First Arrival Time Identification Using Transfer Learning With Continuous Wavelet Transform Feature Images.
IEEE Geosci. Remote. Sens. Lett., 2020

2008
An Improved Tikhonov Regularization Method for Conductivity Tomography Imaging.
Proceedings of the 2008 International Symposium on Computer Science and Computational Technology, 2008


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