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Optics-Free Imaging Using A Self-Consistent Supervised Deep Neural Network

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Abstract

We propose a deep neural network self-consistent supervised model for optics-free image reconstruction. The model learns both the inverse imaging problem as well as the forward to better constrain the reconstruction.

© 2021 The Author(s)

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Poster Presentation

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