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[No title available]
[No authors listed] [No authors listed] PMID: 33686055
Dynamical machine learning volumetric reconstruction of objects' interiors from limited angular views.
Kang I, Goy A, Barbastathis G. Kang I, et al. Among authors: goy a. Light Sci Appl. 2021 Apr 7;10(1):74. doi: 10.1038/s41377-021-00512-x. Light Sci Appl. 2021. PMID: 33828073 Free PMC article.
Recently, it was shown that one effective way to learn the priors for strongly scattering yet highly structured 3D objects, e.g. layered and Manhattan, is by a static neural network [Goy et al. Proc. Natl. Acad. Sci. 116, 19848-19856 (2019)]. ...Through a com …
Recently, it was shown that one effective way to learn the priors for strongly scattering yet highly structured 3D objects, e.g. layered and …
Probing shallower: perceptual loss trained Phase Extraction Neural Network (PLT-PhENN) for artifact-free reconstruction at low photon budget.
Deng M, Goy A, Li S, Arthur K, Barbastathis G. Deng M, et al. Among authors: goy a. Opt Express. 2020 Jan 20;28(2):2511-2535. doi: 10.1364/OE.381301. Opt Express. 2020. PMID: 32121939 Free article.
Deep neural networks (DNNs) are efficient solvers for ill-posed problems and have been shown to outperform classical optimization techniques in several computational imaging problems. In supervised mode, DNNs are trained by minimizing a measure of the difference between th …
Deep neural networks (DNNs) are efficient solvers for ill-posed problems and have been shown to outperform classical optimization techniques …
Digital confocal microscope.
Goy AS, Psaltis D. Goy AS, et al. Opt Express. 2012 Sep 24;20(20):22720-7. doi: 10.1364/OE.20.022720. Opt Express. 2012. PMID: 23037422 Free article.
246 results