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Research and application of neural network approaches to solving image recognition problems

Marina BolsunovskayaPeter the Great St. Petersburg Polytechnic University, 29, Polytechnicheskaya, Saint-Petersburg, 195251, Russian FederationEgor KuzmichevPeter the Great St. Petersburg Polytechnic University, 29, Polytechnicheskaya, Saint-Petersburg, 195251, Russian FederationSvetlana ShirokovaPeter the Great St. Petersburg Polytechnic University, 29, Polytechnicheskaya, Saint-Petersburg, 195251, Russian FederationTojiboy AlmataevAndijаn Machine-Building Institute, 56, Bobur Shoh St., Andijan, 170019, Uzbekistan
E3S Web of Conferencesjournal2022en
ABI

Аннотация

The paper investigates neural network approaches to solving number recognition problems and develops an algorithm for creating authentic datasets. In the course of the work, research and development of an algorithm for creating authentic datasets for solving the problem of number recognition is carried out. When solving image recognition problems, it is advisable to use neural network technologies, but often there is a problem of lack of data to form a full-fledged training sample during recognition. An algorithm has been developed to create a set of artificial data appropriate for use in training neural networks. The recognition of number plates and wagon numbers is assumed to be the scope of application. An algorithm that forms a set of synthetic images marked up for training has been created. The result of the algorithm application is a dataset appropriate for supplementing the training sample when training neural networks in the field of recognition of number plates and wagon numbers.

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