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A ground-based dataset and a diffusion model for on-orbit low-light image enhancement
To evenly sample poses of different orientation and distance without collision, a collision-free working space and pose stratified sampling is proposed.
WHAT TO DO IF SPARSE REPRESENTATION LEARNING FAILS UNEXPECTEDLY?
RISE is based on a complete analysis for the generalizability of data properties for physical systems.
Adversarial twin neural networks: maximizing physics recovery for physical system
Thus, we propose (1) sparsity regularization for the physical model and (2) physical superiority over the virtual model.
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