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Immune response inspired spatial–temporal target detection algorithms with CNN‐UM
Author(s) -
Cserey György,
Falus András,
Roska Tamás
Publication year - 2006
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/cta.341
Subject(s) - computer science , terrain , cellular neural network , algorithm , electronic circuit , template , artificial intelligence , artificial immune system , computer architecture , artificial neural network , engineering , ecology , electrical engineering , biology , programming language
In this paper we show that, similar to the nervous system and the genetic system, the immune system provides a prototype for a ‘computing mechanism.’ We are presenting an immune response inspired algorithmic framework for spatial–temporal target detection applications using CNN technology ( IEEE Trans. Circuits Syst. II 1993; 40 (3):163–173; Foundations and Applications . Cambridge University Press: Cambridge, 2002). Unlike most analogic CNN algorithms ( IEEE Trans. Circuits Syst. 1988; 35 (10):1257–1290; Foundations and Applications . Cambridge University Press: Cambridge, 2002) here we will detect various targets by using a plethora of templates. These algorithms can be implemented successfully only by using a computer upon which thousands of elementary, fully parallel spatial–temporal actions can be implemented in real time. In our tests the results show a statistically complete success rate, and we are presenting a special example of recognizing dynamic objects. Results from tests in a 3D virtual world with different terrain textures are also reported to demonstrate that the system can detect unknown patterns and dynamical changes in image sequences. Applications of the system include in explorer systems for terrain surveillance. Copyright © 2006 John Wiley & Sons, Ltd.