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.
|Number of pages||6|
|Journal||IEEE International Conference on Neural Networks - Conference Proceedings|
|Publication status||Published - Dec 1 2004|
|Event||2004 IEEE International Joint Conference on Neural Networks - Proceedings - Budapest, Hungary|
Duration: Jul 25 2004 → Jul 29 2004
ASJC Scopus subject areas