Recurrent graph optimal transport for learning 3D flow motion in particle tracking
Flow visualization technologies such as particle tracking velocimetry are broadly used for
studying three-dimensional turbulent flow in natural and industrial processes. Despite the …
studying three-dimensional turbulent flow in natural and industrial processes. Despite the …
Machine learning for flow field measurements: a perspective
S Discetti, Y Liu - Measurement Science and Technology, 2022 - iopscience.iop.org
Advancements in machine-learning (ML) techniques are driving a paradigm shift in image
processing. Flow diagnostics with optical techniques is not an exception. Considering the …
processing. Flow diagnostics with optical techniques is not an exception. Considering the …
DeepPTV: Particle tracking velocimetry for complex flow motion via deep neural networks
Particle tracking velocimetry (PTV) is a powerful technique for global and nonintrusive flow
field measurement, which shows a great potential to improve the spatial resolution …
field measurement, which shows a great potential to improve the spatial resolution …
Particle reconstruction of volumetric particle image velocimetry with the strategy of machine learning
Three-dimensional particle reconstruction with limited two-dimensional projections is an
under-determined inverse problem that the exact solution is often difficult to be obtained. In …
under-determined inverse problem that the exact solution is often difficult to be obtained. In …
A 3D reconstruction method of bubble flow field based on multi-view images by bi-direction filtering maximum likelihood expectation maximization algorithm
H Wang, Y Yang, G Dou, J Lou, X Zhu, L Song… - International Journal of …, 2023 - Elsevier
Aiming at the problem of the three-dimensional (3D) reconstruction of bubble flow field, a Bi-
Direction Filtering Maximum Likelihood Expectation Maximization (BDF-MLEM) algorithm …
Direction Filtering Maximum Likelihood Expectation Maximization (BDF-MLEM) algorithm …
Reconstruction of particle image velocimetry data using flow-based features and validation index: a machine learning approach
G Akbari, N Montazerin - Measurement Science and Technology, 2021 - iopscience.iop.org
Reconstruction of flow field from real sparse data by a physics-oriented approach is a
current challenge for fluid scientists in the AI community. The problem includes feature …
current challenge for fluid scientists in the AI community. The problem includes feature …
Solving multiple travelling salesman problem through deep convolutional neural network
Z Ling, Y Zhou, Y Zhang - IET Cyber‐Systems and Robotics, 2023 - Wiley Online Library
The multiple travelling salesman problem (mTSP) is a classical optimisation problem that is
widely applied in various fields. Although the mTSP was solved using both classical …
widely applied in various fields. Although the mTSP was solved using both classical …
A sparse optical flow inspired method for 3D velocimetry
G Lu, A Steinberg, M Yano - Experiments in Fluids, 2023 - Springer
We introduce a three-dimensional three-component particle-based velocimetry method that
expands the methodology of optical flow to three dimensions. The proposed scheme, sparse …
expands the methodology of optical flow to three dimensions. The proposed scheme, sparse …
Volumetric reconstruction of flow particles through light field particle image velocimetry and deep neural network
Tomographic reconstruction of three-dimensional (3D) tracer particle distributions through
light field particle image velocimetry (LF-PIV) faces challenges in low reconstruction …
light field particle image velocimetry (LF-PIV) faces challenges in low reconstruction …
A calibration-informed deep learning model for three-dimensional particle reconstruction of volumetric particle image velocimetry
H Lin, Q Gao - Physics of Fluids, 2024 - pubs.aip.org
Accurately reconstructing three-dimensional particle fields is essential in fluid velocity
measurement research. This study addresses the limitations of current three-dimensional …
measurement research. This study addresses the limitations of current three-dimensional …