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  2. Particle Detection by means of Neural Networks and Synthetic Training Data Refinement in Defocusing Particle Tracking Velocimetry (data)
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    Datenpaket: Particle Detection by means of Neural Networks and Synthetic Training Data Refinement in Defocusing Particle Tracking Velocimetry (data)

    Alternativer Identifier:
    (KITopen-DOI) 10.5445/IR/1000146837
    Verwandter Identifier:
    -
    Ersteller/in:
    Dreisbach, Maximilian https://orcid.org/0000-0001-6308-0982 [Institut für Strömungsmechanik]

    Leister, Robin https://orcid.org/0000-0002-0286-8183 [Institut für Strömungsmechanik]

    Probst, Matthias https://orcid.org/0000-0001-8729-0482 [Institut für Thermische Strömungsmaschinen]

    Friederich, Pascal https://orcid.org/0000-0003-4465-1465 [Institut für Theoretische Informatik]

    Stroh, Alexander [Institut für Strömungsmechanik]

    Kriegseis, Jochen https://orcid.org/0000-0002-2737-2539 [Institut für Strömungsmechanik]
    Beitragende:
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    Titel:
    Particle Detection by means of Neural Networks and Synthetic Training Data Refinement in Defocusing Particle Tracking Velocimetry (data)
    Weitere Titel:
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    Beschreibung:
    (Technical Remarks) This repository contains the supplementary data to our contribution "Particle Detection by means of Neural Networks and Synthetic Training Data Refinement in Defocusing Particle Tracking Velocimetry" to the 2022 Measurement Science and Technology special issue on the topic “Machine Learning and Data Assimilation techniques for fluid flow measurements”. This data includes annotated images used for the training of neural networks for particle detection on DPTV recordings as well as unannotated particle images used for training of the image-to-image translation networks for the generation of refined synthetic training data, as presented in the manuscript. The neural networks for particle detection trained on the aforementioned data are contained in this repository as well. An explanation on the use of this data and the trained neural networks, containing an example script can be found on GitHub (https://github.com/MaxDreisbach/DPTV_ML_Particle_detection)
    Schlagworte:
    Defocusing Particle Tracking Velocimetry
    Synthetic Training Data Refinement
    Particle Detection
    Zugehörige Informationen:
    -
    Sprache:
    -
    Herausgeber/in:
    Karlsruhe Institute of Technology
    Erstellungsjahr:
    Fachgebiet:
    Engineering
    Objekttyp:
    Dataset
    Datenquelle:
    -
    Verwendete Software:
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    Datenverarbeitung:
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    Erscheinungsjahr:
    Rechteinhaber/in:

    Stroh, Alexander
    Förderung:
    -
    Name Speichervolumen Metadaten Upload Aktion
    Status:
    Publiziert
    Eingestellt von:
    kitopen
    Erstellt am:
    Archivierungsdatum:
    2023-06-21
    Archivgröße:
    4,2 GB
    Archiversteller:
    kitopen
    Archiv-Prüfsumme:
    58187a036e9149de4f52b5708f30da84 (MD5)
    Embargo-Zeitraum:
    -