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Proceedings Paper

Random neural network recognition of shaped objects in strong clutter
Author(s): Hakan Bakircioglu; Erol Gelenbe
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Paper Abstract

Detecting objects in images containing strong clutter is an important issue in a variety of applications such as medical imaging and automatic target recognition. Artificial neural networks are used as non-parametric pattern recognizers to cope with different problems due to their inherent ability to learn from training data. In this paper we propose a neural approach based on the Random Neural Network model (Gelenbe 1989, 1990, 1991, 1993), to detect shaped targets with the help of multiple neural networks whose outputs are combined for making decisions.

Paper Details

Date Published: 1 April 1998
PDF: 7 pages
Proc. SPIE 3307, Applications of Artificial Neural Networks in Image Processing III, (1 April 1998); doi: 10.1117/12.304656
Show Author Affiliations
Hakan Bakircioglu, Duke Univ. (United States)
Erol Gelenbe, Duke Univ. (United States)


Published in SPIE Proceedings Vol. 3307:
Applications of Artificial Neural Networks in Image Processing III
Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

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