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Proceedings Paper

Neural networks with optical-correlation inputs for recognizing rotated targets
Author(s): Steven C. Gustafson; David L. Flannery; Darren M. Simon
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Paper Abstract

Backpropagation-trained neural networks with optical correlation inputs are used to predict target rotation and to synthesize simplified optical correlation filters for rotated targets.

Paper Details

Date Published: 1 August 1990
PDF: 9 pages
Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); doi: 10.1117/12.21167
Show Author Affiliations
Steven C. Gustafson, Univ. of Dayton Research Insti (United States)
David L. Flannery, Univ. of Dayton Research Insti (United States)
Darren M. Simon, Univ. of Dayton Research Insti (United States)


Published in SPIE Proceedings Vol. 1294:
Applications of Artificial Neural Networks
Steven K. Rogers, Editor(s)

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