8 citations · 9 across the 2 of their papers we have counts for
4 papers
A Review of Deep-learning-based Seismic Data Denoising and Its Promising Paradigm Shift to Foundation Models
Xintong Dong, Zhengyi Yuan, Changxin Wei +3
Denoising is a long-standing and widely-concerned topic in seismic data processing, for it can significantly increase the signal-to-noise ratio of seismic data. Numerous deep learn…
Light-weighted foundation model for seismic data processing based on representative and non-redundant pre-training dataset
Xintong Dong, Wenshuo Yu, Jun Lin +3
In the fields of computer vision (CV) and remote sensing (RS), foundational models typically follow the "big data + large model parameters" paradigm. However, the application of th…
SAM2-ELNet: Label Enhancement and Automatic Annotation for Remote Sensing Segmentation
Jianhao Yang, Wenshuo Yu, Yuanchao Lv +3
Remote sensing image segmentation is crucial for environmental monitoring, disaster assessment, and resource management, but its performance largely depends on the quality of the d…
MAE-GAN: A Novel Strategy for Simultaneous Super-resolution Reconstruction and Denoising of Post-stack Seismic Profile
Wenshuo Yu, Shiqi Dong, Shaoping Lu +1
Post-stack seismic profiles are images reflecting containing geological structures which provides a critical foundation for understanding the distribution of oil and gas resources.…