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Approaches Taken to Streamline and Consolidate Large Dataset Processing Techniques, with a Focus on Ptychography

Published online by Cambridge University Press:  22 July 2022

Thomas C. Pekin ,
Marcel Schloz ,
Pablo Fernandez Robledo ,
Anton Gladyshev ,
Sherjeel Shabih ,
Benedikt Haas  and
Christoph T. Koch
Thomas C. Pekin*
Affiliation:
Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany
Marcel Schloz
Affiliation:
Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany
Pablo Fernandez Robledo
Affiliation:
Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany
Anton Gladyshev
Affiliation:
Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany
Sherjeel Shabih
Affiliation:
Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany
Benedikt Haas
Affiliation:
Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany
Christoph T. Koch
Affiliation:
Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany
*
*Corresponding author: tcpekin@physik.hu-berlin.de

Abstract

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Type
Artificial Intelligence, Instrument Automation, And High-dimensional Data Analytics for Microscopy and Microanalysis
Information
Microscopy and Microanalysis , Volume 28 , Supplement S1 , August 2022 , pp. 2994 - 2996
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Copyright
Copyright © Microscopy Society of America 2022

References

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The authors acknowledge financial support from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-IDs 414984028 (SFB 1404), 182087777 (SFB 951), and 460197019 (FAIRmat).Google Scholar