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Preprint . 2022
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ZENODO
Preprint . 2022
License: CC BY
Data sources: ZENODO
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Fast Autofocusing using Tiny Networks for Digital Holographic Microscopy

Authors: Stéphane Cuenat; Louis Andréoli; Antoine N.André; Patrick Sandoz; Guillaume J.Laurent; Raphaël Couturier; Maxime Jacquot;

Fast Autofocusing using Tiny Networks for Digital Holographic Microscopy

Abstract

This dataset contains a set of experimental holograms of a pseudo-periodic pattern ranging on 92 \({\mu}m\) with a step of ~1 \({\mu}m\) between each class of holograms. A total of 40,400 holograms are divided in 100 classes each containing a total of 400 experimental holograms. The experiments were carried out on a antivibration table with a DHM (by Lyncee Tec, Switzerland) equipped with a camera with a 5.86 \({\mu}m\) pixel size (Basler acA1920-155um), a hexapode (Newport HXP50-meca) capable of precise motions along the six degrees of freedom and a micro-encoded pattern made in our clean room facility (2 x 2 \(cm^2\), period 9 \({\mu}m\), 12 bits encoding) covered with a uniform 100 nm thick aluminium layer to obtain a phase object. This pseudo periodic pattern was observed with a MO (Leica, mag 10x, NA=0.32) at wavelength \(\lambda \) = 674.99 nm. A second file (mapping file) gives the mapping in \({\mu}m\) for each class of 400 holograms: holos_04_06_2021_hxp_dhm_100classes400Measures_positionZ.csv.

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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