NDLI: Neural networks for calibration tomography

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Neural networks for calibration tomography

Content Provider	NASA Technical Reports Server (NTRS)
Author	Decker, Arthur
Copyright Year	1993
Description	Artificial neural networks are suitable for performing pattern-to-pattern calibrations. These calibrations are potentially useful for facilities operations in aeronautics, the control of optical alignment, and the like. Computed tomography is compared with neural net calibration tomography for estimating density from its x-ray transform. X-ray transforms are measured, for example, in diffuse-illumination, holographic interferometry of fluids. Computed tomography and neural net calibration tomography are shown to have comparable performance for a 10 degree viewing cone and 29 interferograms within that cone. The system of tomography discussed is proposed as a relevant test of neural networks and other parallel processors intended for using flow visualization data.
File Size	616033
Page Count	14
File Format	PDF
Alternate Webpage(s)	http://archive.org/details/NASA_NTRS_Archive_19930017717
Archival Resource Key	ark:/13960/t0cv9f02k
Language	English
Publisher Date	1993-06-01
Access Restriction	Open
Subject Keyword	Neural Nets Calibrating Flow Visualization Computer Aided Tomography Holographic Interferometry Density Distribution Parallel Processing Computers X Ray Density Measurement Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science
Content Type	Text
Resource Type	Article

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