5 papers
DTurb: Depth-Aware Simulation and Decoupled Learning for Single-Frame Atmospheric Turbulence Mitigation
Zixiao Hu, Tianyu Li, Guoqing Wang +4
Single-frame atmospheric turbulence mitigation is inherently ill-posed due to spatially varying blur coupled with non-rigid geometric distortion. Existing end-to-end approaches tra…
DSPR: Dual-Stream Physics-Residual Networks for Trustworthy Industrial Time Series Forecasting
Yeran Zhang, Pengwei Yang, Guoqing Wang +1
Accurate forecasting of industrial time series requires balancing predictive accuracy with physical plausibility under non-stationary operating conditions. Existing data-driven mod…
AlignVAR: Towards Globally Consistent Visual Autoregression for Image Super-Resolution
Cencen Liu, Dongyang Zhang, Wen Yin +6
Visual autoregressive (VAR) models have recently emerged as a promising alternative for image generation, offering stable training, non-iterative inference, and high-fidelity synth…
Hybrid Boundary Physics-Informed Neural Networks for Solving Navier-Stokes Equations with Complex Boundary
Chuyu Zhou, ianyu Li, Chenxi Lan +7
Physics-informed neural networks (PINN) have achieved notable success in solving partial differential equations (PDE), yet solving the Navier-Stokes equations (NSE) with complex bo…
Ultra-Low Complexity On-Orbit Compression for Remote Sensing Imagery via Block Modulated Imaging
Zhibin Wang, Yanxin Cai, Jiayi Zhou +6
The growing field of remote sensing faces a challenge: the ever-increasing size and volume of imagery data are exceeding the storage and transmission capabilities of satellite plat…