(untitled) (Transport systems and technologies, 2021)
This article considers the problems of modern models and methods of recognition of information and images, the analogy of learning parallel-hierarchical networks with RBF networks. During the analysis, it was determined that image processing using the mask method does not use all the power of multi-core systems. The analysis of parallel-hierarchical transformation and image processing is carried out. The analysis of the mathematical model of parallel-hierarchical transformation for speed increase by means of parallel transformation is carried out. The algorithm was simulated using the C # language, and artificially created images using microwave were used for the test. The simulation was performed for complete PI conversion, the simulation results are shown in the tables. Parallel-hierarchical transformation for image processing has great potential in transport systems, it can be used in tasks where it is necessary to quickly analyze images from the camera, such as the presence of obstacles in the trajectory of traffic and collision avoidance, analysis of asphalt damage on the trajectory and suspension adjustment to level the effect. The results obtained in the modeling process allow us to conclude that the speed of parallel-hierarchical transformation in image processing problems.