MODEL OF A GROUND OBJECT RECOGNITION SYSTEM BASED ON A NEURAL NETWORK
At present, the problem of effective detection and recognition of ground objects on the ground by the artificial intelligence system of an unmanned aerial vehicle has not been solved. The article proposes a model of a ground object recognition system based on a convolutional neural network with the YOLO-V3 architecture, which can be used as part of an artificial intelligence system for an unmanned aerial vehicle.