Cellular Neural Networks and their Application CNNA2002, Germany, 1 - 04 July 2002, vol.7, pp.391-398
Conference Paper / Full Text
Istanbul University Affiliated:
In this paper, Multi-Level Genetic Cellular Neural Networks
(ML-GCNN) are applied to the geophysical problem
of potential anomaly separation and satisfactory results are
obtained, compared to classical deterministic approaches.
ML-GCNN is a stochastic image processing technique
which is based on template optimisation using
neighbourhood relationships of the pixels. The residual
anomaly separation used in location decisions is one of the
main problems in geophysics. The method proposed here is
used in evaluating the Dumluca iron ore region of Turkey.