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cs.CV2020
Memory-efficient Learning for Large-scale Computational Imaging
Michael Kellman, Kevin Zhang, Jon Tamir +3
Critical aspects of computational imaging systems, such as experimental design and image priors, can be optimized through deep networks formed by the unrolled iterations of classic…
eess.IV2020
Deep Phase Decoder: Self-calibrating phase microscopy with an untrained deep neural network
Emrah Bostan, Reinhard Heckel, Michael Chen +2
Deep neural networks have emerged as effective tools for computational imaging including quantitative phase microscopy of transparent samples. To reconstruct phase from intensity,…