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

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

Авторы

Ивлиев Евгений Андреевич
магистрант кафедры «Базовая кафедра «АМиУ»
Россия, Донской государственный технический университет
123ivliev123@mail.ru
Обухов Павел Серафимович
кандидат технических наук, доцент, декан факультета «Автоматизация мехатроника и управление»
Россия, Донской государственный технический университет
pobuhov@spark-mail.ru

Аннотация

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.

Ключевые слова

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

Финансирование

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)

Рекомендуемая ссылка

Ивлиев Евгений Андреевич, Обухов Павел Серафимович. Application of deep neural networks for identification of alphanumeric information from baggage tags at airport // Современные технологии управления. ISSN 2226-9339. — #3 (93). Номер статьи: 9305. Дата публикации: 02.10.2020. Режим доступа: https://sovman.ru/en/article/9305/

Authors

Ivliyev Yevgeniy Andreyevich
Master's student of the Department "Basic Department" AMiU "
Russia, Don State Technical University
123ivliev123@mail.ru
Obukhov Pavel Serafimovich
Candidate of Technical Sciences, Associate Professor, Dean of the Faculty "Automation of Mechatronics and Control"
Russia, Don State Technical University
pobuhov@spark-mail.ru

Abstract

Keywords

Suggested citation

Ivliyev Yevgeniy Andreyevich, Obukhov Pavel Serafimovich. // Modern Management Technology. ISSN 2226-9339. — #3 (93). Art. #  9305. Date issued: 02.10.2020. Available at: https://sovman.ru/en/article/9305/


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Библиографический список

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