activity
20232025
most citedDeepPhysiNet: Bridging Deep Learning and Atmospheric Physics for Accurate and Continuous Weather Modeling

7 citations · 18 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2025

DynamicVis: Dynamic Visual Perception for Efficient Remote Sensing Foundation Models

Keyan Chen, Chenyang Liu, Bowen Chen +4

The advancement of RS technology has enabled high-resolution Earth observation; however, interpreting these images using modern VFMs remains a significant challenge. Unlike object-…

cs.CV2025

Kolmogorov Arnold Neural Interpolator for Downscaling and Correcting Meteorological Fields from In-Situ Observations

Zili Liu, Hao Chen, Lei Bai +3

Obtaining accurate weather forecasts at station locations is a critical challenge due to systematic biases arising from the mismatch between multi-scale, continuous atmospheric cha…

physics.ao-ph2024

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…

cs.CV2024★ 3 cited

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…

cs.CV2024★ 4 cited

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…

cs.CV2024

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…

physics.ao-ph2024★ 7 cited

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…

cs.CV2023★ 4 cited

Time Travelling Pixels: Bitemporal Features Integration with Foundation Model for Remote Sensing Image Change Detection

Keyan Chen, Chengyang Liu, Wenyuan Li +5

Change detection, a prominent research area in remote sensing, is pivotal in observing and analyzing surface transformations. Despite significant advancements achieved through deep…