Results 51 to 60 of about 7,807,536 (173)
Ab initio compressive phase retrieval
, 2008 Any object on earth has two fundamental properties: it is finite, and it is made of atoms. Structural information about an object can be obtained from diffraction amplitude measurements that account for either one of these traits. Nyquist-sampling of the
Marchesini, S.
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Lensless Three-Dimensional Quantitative Phase Imaging Using Phase Retrieval Algorithm
Journal of Imaging, 2020 Quantitative phase imaging (QPI) techniques are widely used for the label-free examining of transparent biological samples. QPI techniques can be broadly classified into interference-based and interferenceless methods.
V. Anand +4 more
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Low Photon Count Phase Retrieval Using Deep Learning. [PDF]
Physical Review Letters, 2018 Imaging systems' performance at low light intensity is affected by shot noise, which becomes increasingly strong as the power of the light source decreases.
A. Goy +3 more
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Solving (most) of a set of quadratic equalities: Composite optimization for robust phase retrieval [PDF]
Information and Inference A Journal of the IMA, 2017 We develop procedures, based on minimization of the composition $f(x) = h(c(x))$ of a convex function $h$ and smooth function $c$, for solving random collections of quadratic equalities, applying our methodology to phase retrieval problems.
John C. Duchi, Feng Ruan
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Phase retrieval by power iterations
, 2012 I show that the power iteration method applied to the phase retrieval problem converges under special conditions. One is given the relative phases between small non-overlapping groups of pixels of a recorded intensity pattern, but no information on the ...
Marchesini, Stefano
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, 2021 We study a bandit version of phase retrieval where the learner chooses actions $(A_t)_{t=1}^n$ in the $d$-dimensional unit ball and the expected reward is $\langle A_t, _\star\rangle^2$ where $ _\star \in \mathbb R^d$ is an unknown parameter vector. We prove that the minimax cumulative regret in this problem is $\smash{\tilde (d \sqrt{n})}$, which
Lattimore, Tor, Hao, Botao
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Online Regularization by Denoising with Applications to Phase Retrieval [PDF]
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 2019 Regularization by denoising (RED) is a powerful framework for solving imaging inverse problems. Most RED algorithms are iterative batch procedures, which limits their applicability to very large datasets.
Zihui Wu +3 more
semanticscholar +1 more source
Optics Express, 2019 We propose a label enhanced and patch based deep learning phase retrieval approach which can achieve fast and accurate phase retrieval using only several fringe patterns as training dataset.
Jiashuo Shi +4 more
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Phase Retrieval via Randomized Kaczmarz: Theoretical Guarantees
, 2017 We consider the problem of phase retrieval, i.e. that of solving systems of quadratic equations. A simple variant of the randomized Kaczmarz method was recently proposed for phase retrieval, and it was shown numerically to have a computational edge over ...
Tan, Yan Shuo, Vershynin, Roman
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Phase Retrieval Using Conditional Generative Adversarial Networks [PDF]
International Conference on Pattern Recognition, 2019 In this paper, we propose the application of conditional generative adversarial networks to solve various phase retrieval problems. We show that including knowledge of the measurement process at training time leads to an optimization at test time that is
Tobias Uelwer +2 more
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