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Data · dataset · 2023

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

Listed in RADAR and RADAR4Memory — shown once because both records carry DOI 10.35097/1333

Description

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 (github.com/MaxDreisbach/DPTV_ML_Particle_detection)

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Fluid mechanics and thermal engineering 73% · Image 65%
Provenance · 2 source records, 13 field assertions
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RADAR10.35097/133313 d agoJSON v1
RADAR4Memory10.35097/133313 d agoJSON v1
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