7 citations · 18 across the 8 of their papers we have counts for
5 papers · 1 filter
MambaDS: Near-Surface Meteorological Field Downscaling with Topography Constrained Selective State Space Modeling
Zili Liu, Hao Chen, Lei Bai +4
In an era of frequent extreme weather and global warming, obtaining precise, fine-grained near-surface weather forecasts is increasingly essential for human activities. Downscaling…
RSMamba: Remote Sensing Image Classification with State Space Model
Keyan Chen, Bowen Chen, Chenyang Liu +3
Remote sensing image classification forms the foundation of various understanding tasks, serving a crucial function in remote sensing image interpretation. The recent advancements…
Observation-Guided Meteorological Field Downscaling at Station Scale: A Benchmark and a New Method
Zili Liu, Hao Chen, Lei Bai +6
Downscaling (DS) of meteorological variables involves obtaining high-resolution states from low-resolution meteorological fields and is an important task in weather forecasting. Pr…
Learning to detect cloud and snow in remote sensing images from noisy labels
Zili Liu, Hao Chen, Wenyuan Li +5
Detecting clouds and snow in remote sensing images is an essential preprocessing task for remote sensing imagery. Previous works draw inspiration from semantic segmentation models…
DeepPhysiNet: Bridging Deep Learning and Atmospheric Physics for Accurate and Continuous Weather Modeling
Wenyuan Li, Zili Liu, Keyan Chen +4
Accurate weather forecasting holds significant importance to human activities. Currently, there are two paradigms for weather forecasting: Numerical Weather Prediction (NWP) and De…