We describe a new neural network designed to solve the correspondence problem of particle-tracking velocimetry. Given two successive pictures of marker-particles suspended in a fluid, it matches their images by approximately duplicating the fluid motion. We present the results of efficiency tests that reveal the excellence of its performance and its stability with respect to the presence of unmatchable particle images. We compare its success rate in image matching to that of the neural network of Grant and Pan (1995), and observe that it produces better results when the flows have more important changes in direction. It has the important advantages over the latter, of being better adapted to benefit from parallel computing, and of being self-starting, i.e. of not requiring to be taught about the fluid flow in advance.
Experiments in Fluids – Springer Journals
Published: Mar 5, 1999
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera