Localisation of archeological sites using multi-level cellular neural networks

In this paper, a supervised algorithm, Mufti-Level Cellular Neural Network (ML-CNN) is introduced, developed and then applied to archeological ruins of the Hittite Empire in Turkey. ML-CNN is a stochastic image processing technique which is based on template optimisation using neighbourhood relationships of the pixels. Hittite civilization sites are among the most important archeological locations in history, one reason among others being that written documentation was first produced by them. The historical sight under investigation in this paper with the Mufti-Level CNN approach is the buried walls of the Hittite civilization in Sivas-Altinyayla region of Turkey.Int Inst Informat & System; World Org System & Cybernet; Ctr Syst Studies; Syst Soc Poland; Soc Appl Syst Res; Slovenian Artificial Intelligence Soc; Simon Bolivar Univ; Polish Syst Soc; Italian Soc System; Int Soc Syst Sci; Int Syst Inst; Int Federat Syst Res; Cybernet & Human Knowing, Journal Second Order Cybernet & Cybersemiot; Blaise Pascal Univ, Engineer Sci Inst, CUST; Univ Las Palmas Gran Canaria, Concurrency & Architecture Grp, Telemat Engn Dept; Tunisian Sci Soc; Acad Non Linear Sci; San Luis Natl Univ, Lab Res Computat Intelligence, Dept Informat; Amer Soc Cybernet (Canada); Wolfram Res Inc; IEEE Comp Soc, Venezuela Chapter; Steacie Inst Molec Sci; Natl Res Council Canad