Feature extraction CNN algorithms for artificial immune systems

Gy Cserey, A. Falus, W. Porod, T. Roska

Research output: Contribution to journalConference article

7 Citations (Scopus)


In this paper, we introduce some CNN and analogic feature extraction algorithms for artificial immune systems, which are able to convert grayscale or color to binary images storing as much information as possible for further processing. We define a statistical property called immune histogram based on sub-patterns of these images. Our results and measurements show that these algorithms can be implemented in real-time applications. A sample application, which detects new textures in a familiar environment, is also presented.

Original languageEnglish
Pages (from-to)147-152
Number of pages6
JournalIEEE International Conference on Neural Networks - Conference Proceedings
Publication statusPublished - Dec 1 2004
Event2004 IEEE International Joint Conference on Neural Networks - Proceedings - Budapest, Hungary
Duration: Jul 25 2004Jul 29 2004

ASJC Scopus subject areas

  • Software

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