Random neural network recognition of shaped objects in strong clutter

Hakan Bakircioglu; Erol Gelenbe

doi:10.1117/12.304656

1 April 1998 Random neural network recognition of shaped objects in strong clutter

Hakan Bakircioglu, Erol Gelenbe

Proceedings Volume 3307, Applications of Artificial Neural Networks in Image Processing III; (1998) https://doi.org/10.1117/12.304656
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

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.

Citation Download Citation

Hakan Bakircioglu and Erol Gelenbe "Random neural network recognition of shaped objects in strong clutter", Proc. SPIE 3307, Applications of Artificial Neural Networks in Image Processing III, (1 April 1998); https://doi.org/10.1117/12.304656

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