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Jul, 2024
用残差 Beylkin-Coifman-Rokhlin 神经网络解决显微镜去卷积的逆问题
Solving the inverse problem of microscopy deconvolution with a residual Beylkin-Coifman-Rokhlin neural network
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Rui Li, Mikhail Kudryashev, Artur Yakimovich
TL;DR
利用物理约束,我们的模型在专业领域的神经网络候选者中显著减少了冗余参数,并取得了高效率和优越性能。
Abstract
optic deconvolution
in light
microscopy
(LM) refers to recovering the object details from images, revealing the ground truth of samples. Traditional explicit methods in LM rely on the point spread function (PSF)
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