A.N. Shtanko1

1 National Research Nuclear University "MEPhI" (NRNU MEPHI) (Moscow, Russia)

Problem statement. While developing new methods, algorithms and implementations in the field of convolutional neural networks it is vital to know the existing works presented in academic papers, as well as protected by patents. Therefore, it is necessary to analyze and systematize existing solutions based on convolutional neural networks protected by patents.

Objective. To find and analyze the inventions and utility models in the area of convolutional neural networks protected by Russian patent documents.

Results. Solutions in the area of neural networks protected by patents were found and analyzed. An increase in the number of patented solutions in recent years was shown, as well as the emergence of solutions based on convolutional neural networks. Abstracts of the inventions based on convolutional neural networks were analyzed, and a significant number of solutions were found specifically in the medical field, and in them the neural networks are most often used for classification, segmentation or feature extraction on various images or video sequence frames. In the patented solutions neural networks are used in several ways: the application of known solutions in new areas, invention of new methods and neural network solutions for a particular application problem, development of new neural network methods of general application.

Practical significance. These results can be used to evaluate the development of the field of convolutional neural networks when planning research and development in this area.

Shtanko A.N. Analysis of patented inventions and utility models based on convolutional neural networks. Neurocomputers. 2022. V. 24. № 4. Р. 5-17. DOI: https://doi.org/10.18127/j19998554-202204-01 (in Russian)

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