2 citations · 4 across the 5 of their papers we have counts for
5 papers
Artificial Intelligence for Subsurface Imaging Understanding: A Decade Review of Challenges, Methods, Benchmarks, and Outlook
Yimin Dou, Xinming Wu, Hui Gao +9
Subsurface imaging interpretation bridges observed geophysical data and quantitative geological models, supporting hydrocarbon exploration, CO2 storage assessment, and geohazard mo…
Implicit Structural Modeling via Generative Diffusion Frameworks
Yimin Dou, Xinming Wu, Zhixiang Guo +2
Implicit structural modeling can support understanding subsurface spatial configurations, revealing patterns of geological evolution, and enabling quantitative simulation of geolog…
Geological Everything Model 3D: A Promptable Foundation Model for Unified and Zero-Shot Subsurface Understanding
Yimin Dou, Xinming Wu, Nathan L Bangs +4
Understanding Earth's subsurface is critical for energy transition, natural hazard mitigation, and planetary science. Yet subsurface analysis remains fragmented, with separate mode…
Cross-Domain Foundation Model Adaptation: Pioneering Computer Vision Models for Geophysical Data Analysis
Zhixiang Guo, Xinming Wu, Luming Liang +3
We explore adapting foundation models (FMs) from the computer vision domain to geoscience. FMs, large neural networks trained on massive datasets, excel in diverse tasks with remar…
Intelligent Traffic Monitoring with Distributed Acoustic Sensing
Dongzi Xie, Xinming Wu, Zhixiang Guo +3
Distributed Acoustic Sensing (DAS) is promising for traffic monitoring, but its extensive data and sensitivity to vibrations, causing noise, pose computational challenges. To addre…