Artificial immune systems based novelty detection with CNN-UM

In this paper, we show that the earlier presented immune response inspired algorithmic framework in the work of Gy. Cserey et al. (2006, 2004) for spatial-temporal target detection applications using CNN technology by T. Roska and L.O. Chua (1993, 2002) and T. Roska (2002) can be implemented on the latest CNN-UM chip (Acel6k) by A. Rodriguez-Vazquez (2004) and Bi-i system by A. Zarandy and C. Rekcezky (2005). The implementation of the algorithm is real-time and able to detect novelty events in image flows reliably, running 10000 templates/s with video-frame (25 frame/s) speed and on image size of 128 times 128. Besides that some results of the implementation of this AIS model and its application for natural image flows are shown, the realized adaptation and mutation methods are also introduced.