1 April 1998 Random neural network recognition of shaped objects in strong clutter
Author Affiliations +
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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hakan Bakircioglu, Hakan Bakircioglu, Erol Gelenbe, 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); doi: 10.1117/12.304656; https://doi.org/10.1117/12.304656

Back to Top