Application of deep neural networks for identification of alphanumeric information from baggage tags at airport


Master's student of the Department "Basic Department" AMiU "
Russia, Don State Technical University
[email protected]

Candidate of Technical Sciences, Associate Professor, Dean of the Faculty "Automation of Mechatronics and Control"
Russia, Don State Technical University
[email protected]


The article is devoted to the development and analysis of methods of identifying dynamic objects. A neural network with the architecture of SSD InceptionV2 has been developed to solve the problem of detecting luggage tags and barcodes. Several approaches are considered to solve the problem of identifying digital-letter information: Tesseract, SSD InceptionV2, OpenCV and a fully connected neural network. The operability of the methods on real images has been tested.


computer vision, neural network, barcode, IATA airport code, TensorFlow, OpenCV, Python.

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The article was prepared with the support and within the framework of the DR-2020 event "International Competition of Scientific Works and Projects of Young Researchers" Digital Region - 2020 "" (Science and Education on-line)

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Ivliyev Yevgeniy Andreyevich , Obukhov Pavel Serafimovich
Application of deep neural networks for identification of alphanumeric information from baggage tags at airport// Modern Management Technology. ISSN 2226-9339. – #3 (93). Art. # 9305. Date issued: . Available at:

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