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Proceedings Paper

Decision making using conventional calculations versus neural networks for substance identification
Author(s): Thomas Gill Miller
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Paper Abstract

Neural network calculations are compared to conventional probability calculations for decision making in an explosives detection system. The explosives detection system, which has been tested in the laboratory, is a pulsed fast neutron spectrometer that measures the attenuation of neutrons for a particular suitcase loading. The attenuation curves along with the measured total cross sections are used to determine the amount of hydrogen, carbon, nitrogen and oxygen in volume increments through the suitcase. This information is used to determine a probability of detection (of explosives) versus a probability of false alarm curve. The same information is used in a neural network program to determine its effectiveness in predicting the presence of explosives. The neural network was trained from computer generated data and tested on extrapolated laboratory data.

Paper Details

Date Published: 1 February 1994
PDF: 13 pages
Proc. SPIE 2093, Substance Identification Analytics, (1 February 1994); doi: 10.1117/12.172499
Show Author Affiliations
Thomas Gill Miller, Tensor Technology Inc. (United States)

Published in SPIE Proceedings Vol. 2093:
Substance Identification Analytics
James L. Flanagan; Richard J. Mammone; Albert E. Brandenstein; Edward Roy Pike M.D.; Stelios C. A. Thomopoulos; Marie-Paule Boyer; H. K. Huang; Osman M. Ratib, Editor(s)

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