DEEP NEURAL NETWORK AND THEIR PROBLEMS
The article deals with deep learning neural networks and the problem associated with the inaccuracy of the output data with a certain deception. The principle of DNN operation is characterized. Both methods of deception are described, and examples are shown, and the principles by which it works are clearly spelled out. Based on the data obtained as a result of the study, it is concluded that at present, along with the fact that scientists recognize the fragility of DNN and their dependence on large amounts of data, most of them say that the technique is here to stay.