Adaptive Correction of the Multi-Cascade Detector of Biomorphic Artificial Intelligence System for Pattern Recognition Problems

This paper investigates the adaptive correction of a multistage detector in a biomorphic artificial intelligence system for pattern recognition problems. A distinctive feature of this system is its imitation of the hierarchical information processing observed in living systems, such as in the visual cortex of the brain. As part of this study, an algorithm for correcting the results of a multistage detector was tested, and conclusions about the outcomes of its application were formulated.