Particle detection by means of neural networks and synthetic training data refinement in defocusing particle tracking velocimetry | Zendy

Maximilian Dreisbach | Zendy; Robin Leister | Zendy; Matthias Probst | Zendy; Pascal Friederich | Zendy; Alexander Stroh | Zendy; Jochen Kriegseis | Zendy

Open Access

Particle detection by means of neural networks and synthetic training data refinement in defocusing particle tracking velocimetry

Author(s) -

Maximilian Dreisbach,

Robin Leister,

Matthias Probst,

Pascal Friederich,

Alexander Stroh,

Jochen Kriegseis

Publication year - 2022

Publication title -

measurement science and technology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.48

H-Index - 136

eISSN - 1361-6501

pISSN - 0957-0233

DOI - 10.1088/1361-6501/ac8a09

Subject(s) - artificial intelligence , computer science , artificial neural network , robustness (evolution) , synthetic data , particle tracking velocimetry , false positive paradox , particle image velocimetry , range (aeronautics) , tracking (education) , pattern recognition (psychology) , computer vision , physics , materials science , psychology , pedagogy , biochemistry , chemistry , turbulence , composite material , gene , thermodynamics

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