End-to-End Deep Learning Pipeline for Real-Time Processing of Surface Scattering Data at Synchrotron Facilities

Vladimir Starostin; Linus Pithan; Alessandro Greco; Valentin Munteanu; Alexander Gerlach; Alexander Hinderhofer; Frank Schreiber

doi:10.1080/08940886.2022.2112499

JOURNAL ARTICLE

End-to-End Deep Learning Pipeline for Real-Time Processing of Surface Scattering Data at Synchrotron Facilities

Vladimir Starostin Linus Pithan Alessandro Greco Valentin Munteanu Alexander Gerlach Alexander Hinderhofer Frank Schreiber

Year: 2022 Journal: Synchrotron Radiation News Vol: 35 (4)Pages: 21-27 Publisher: Taylor & Francis

DOI: 10.1080/08940886.2022.2112499

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Keywords:

Pipeline (software) Synchrotron Synchrotron radiation Scattering Surface (topology) Materials science Computer science Optics Physics Geometry Operating system

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Electron and X-Ray Spectroscopy Techniques

Physical Sciences → Materials Science → Surfaces, Coatings and Films

Advanced X-ray and CT Imaging

Physical Sciences → Engineering → Biomedical Engineering

Particle Detector Development and Performance

Physical Sciences → Physics and Astronomy → Nuclear and High Energy Physics

End-to-End Deep Learning Pipeline for Real-Time Processing of Surface Scattering Data at Synchrotron Facilities

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