Learning from simulation: An end-to-end deep-learning approach for computational ghost imaging

Short summary

A one-step end-to-end neural network trained solely on simulation data can reconstruct 2D images from 1D bucket signals in computational ghost imaging, eliminating the need for illumination pattern sequences.

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