Joongmoo Byun

According to our database, Joongmoo Byun authored at least 11 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Near-Offset Gap Trace Extrapolation Based on Self-Supervised Learning.

Jiho Park, Sooyoon Kim, Soon Jee Seol, Joongmoo Byun

IEEE Trans. Geosci. Remote. Sens., 2024

Transfer Learning-Based Seismic Phase Detection Algorithm for Distributed Acoustic Sensing Microseismic Data.

Yonggyu Choi, Soon Jee Seol, Joongmoo Byun

IEEE Trans. Geosci. Remote. Sens., 2024

2023

Explainable Deep Learning for Supervised Seismic Facies Classification Using Intrinsic Method.

Kyubo Noh, Dowan Kim, Joongmoo Byun

IEEE Trans. Geosci. Remote. Sens., 2023

First-Break Picking Method Based on the Difference Between Multiwindow Energy Ratios.

Dowan Kim, Yonghwan Joo, Joongmoo Byun

IEEE Trans. Geosci. Remote. Sens., 2023

Interpretation of Frequency-Domain Airborne Electromagnetic Data Based on the Deep Neural Network Incorporating Topographic Information.

Minkyu Bang, Soon Jee Seol, Joongmoo Byun

IEEE Trans. Geosci. Remote. Sens., 2023

Cross-Streamer Wavefield Reconstruction of a Towed Streamer System Using Bidirectional LSTM Networks With a Traces-to-Trace Approach.

Zeu Yeeh, Daeung Yoon, Joongmoo Byun

IEEE Geosci. Remote. Sens. Lett., 2023

2022

Impedance Inversion Based on Domain Adaptation Technique With Reconstruction.

Jeonghun Yoo, Dowan Kim, Junhwan Choi, Joongmoo Byun

IEEE Geosci. Remote. Sens. Lett., 2022

Bayesian Uncertainty Estimation for Deep Learning Inversion of Electromagnetic Data.

Seokmin Oh, Joongmoo Byun

IEEE Geosci. Remote. Sens. Lett., 2022

Selection of Augmented Data for Overcoming the Imbalance Problem in Facies Classification.

Dowan Kim, Joongmoo Byun

IEEE Geosci. Remote. Sens. Lett., 2022

2021

Seismic Data Reconstruction Using Deep Bidirectional Long Short-Term Memory With Skip Connections.

Daeung Yoon, Zeu Yeeh, Joongmoo Byun

IEEE Geosci. Remote. Sens. Lett., 2021

2019

Salt Delineation From Electromagnetic Data Using Convolutional Neural Networks.

Seokmin Oh, Kyubo Noh, Daeung Yoon, Soon Jee Seol, Joongmoo Byun

IEEE Geosci. Remote. Sens. Lett., 2019