CONVEX OPTIMIZATION FOR ADDITIVE NOISE REDUCTION IN QUANTITATIVE COMPLEX OBJECT WAVE RETRIEVAL USING COMPRESSIVE OFF-AXIS DIGITAL HOLOGRAPHIC IMAGING

Convex optimization for additive noise reduction in quantitative complex object wave retrieval using compressive off-axis digital holographic imaging

Image denoising is one of the important problems in the research field of computer vision, artificial intelligence, 3D vision, and image processing, where the fundamental aim is to recover the original image features from a noisy contaminated image.The camera sensor additive noise present in the holographic recording process reduces the quality of

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Physics-informed deep learning for incompressible laminar flows

ABSTRACT: Physics-informed deep learning has drawn tremendous interest in recent years to solve computational physics problems, whose basic concept is to embed physical laws to constrain/inform neural networks, with the need of less data for training a reliable model.This can be achieved by incorporating the residual of physics equations into the l

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Probable edge defect in Acrysof single-piece intraocular lens

The purpose of this article is to report an edge defect in single-piece hydrophobic acrylic intraocular lens (IOL) observed during a 2000 dodge durango catalytic converter routine phacoemulsification procedure.The chip was successfully removed intraoperatively with a McPherson′s forceps.However, six months postoperatively patient complained

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