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Student-Teacher Learning from Clean Inputs to Noisy Inputs
Feature-based student-teacher learning, a training method that encourages the student's hidden features to mimic those of the teacher network, is empirically successful in transferring the knowledge from a pre-trained teacher network to the student network.
Rethinking Atmospheric Turbulence Mitigation
We demonstrate how a simple prior can outperform state-of-the-art blind deconvolution methods.
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