An artificial neural network for double exposure PIV image analysis

An artificial neural network for double exposure PIV image analysis  This note presents a back propagation neural network for PIV image analysis. Unlike the conventional auto-correlation method that identifies one pair of image out of the picture, the proposed network distinguishes all the image pairs in the measurement area and provides different labels for each pair. Experimental investigations show good agreement with the auto-correlation process for the uniform flow measurement, and a 78.1% success ratio for the stagnation flow. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Experiments in Fluids Springer Journals

An artificial neural network for double exposure PIV image analysis

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Publisher
Springer-Verlag
Copyright
Copyright © 1998 by Springer-Verlag Berlin Heidelberg
Subject
Engineering; Engineering Fluid Dynamics; Fluid- and Aerodynamics; Engineering Thermodynamics, Heat and Mass Transfer
ISSN
0723-4864
eISSN
1432-1114
D.O.I.
10.1007/s003480050185
Publisher site
See Article on Publisher Site

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