ADAPTATION OF HYBRID NEURO-FUZZY NETWORKS FOR CLASSIFICATION OF GROUND TARGETS IN THE ONBOARD COMPUTER SYSTEM OF MILITARY ROBOTIC SYSTEMS
Automation of classification processes for enemy ground targets that are displayed on photographic film or in streaming video received from technical vision systems is discussed in the article. Artificial intelligence methods, which are known to have a high speed of data processing and reliability of situation assessment, are proposed to be used to increase the level of automation of processing (classification) of images of ground objects and achieve the required quality (reliability) of classification of enemy weapons objects. The issues of adaptation (configuration) of the hybrid neuro- fuzzy network apparatus for solving the problem of classification of explored ground targets in the on- board computer system of military air robotic complex are indicated.