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Neuro-Symbolic Artificial Intelligence: Application for Control the Quality of Product Labeling

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Open Semantic Technologies for Intelligent System (OSTIS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1282))

Abstract

The paper presents the implementation of an intelligent decision support system (IDSS) to solve a real manufacturing problem at JSC “Savushkin Product”. The proposed system is intended to control the quality of product labeling, based on neuro-symbolic artificial intelligence, namely integrating deep neural networks and semantic models. The system perform localization and recognition of images from a high-speed video stream and is based on several deep neural networks. Semantic networks fulfill intelligent processing of recognition results in order to generate final decision as regards the state of the production conveyor. We demonstrate the performance of the proposed technique in the real production process. The main contribution of this paper is a novel view at the creation of a real intelligent decision support system, which combines bio inspired approach, namely neural networks and conventional technique, based on a knowledge base.

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Author information

Authors and Affiliations

  1. Brest State Technical University, Brest, Belarus

    Vladimir Golovko & Aliaksandr Kroshchanka

  2. Pope John Paul II State School of Higher Vocational Education in Biala Podlaska, Biala Podlaska, Poland

    Vladimir Golovko

  3. Belarusian State University of Informatics and Radioelectronics, Minsk, Belarus

    Mikhail Kovalev

  4. JSC “Savushkin Product”, Brest, Belarus

    Valery Taberko & Dzmitry Ivaniuk

Authors
  1. Vladimir Golovko
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  2. Aliaksandr Kroshchanka
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  3. Mikhail Kovalev
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  4. Valery Taberko
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  5. Dzmitry Ivaniuk
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Corresponding author

Correspondence to Mikhail Kovalev .

Editor information

Editors and Affiliations

  1. Belarusian State University of Informatics and Radioelectronics, Minsk, Belarus

    Vladimir Golenkov

  2. Department of Information Systems Management, Belarusian State University, Minsk, Belarus

    Victor Krasnoproshin

  3. Brest State Technical University, Brest, Belarus

    Vladimir Golovko

  4. Belarusian State University of Informatics and Radioelectronics, Minsk, Belarus

    Elias Azarov

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Golovko, V., Kroshchanka, A., Kovalev, M., Taberko, V., Ivaniuk, D. (2020). Neuro-Symbolic Artificial Intelligence: Application for Control the Quality of Product Labeling. In: Golenkov, V., Krasnoproshin, V., Golovko, V., Azarov, E. (eds) Open Semantic Technologies for Intelligent System. OSTIS 2020. Communications in Computer and Information Science, vol 1282. Springer, Cham. https://doi.org/10.1007/978-3-030-60447-9_6

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  • DOI: https://doi.org/10.1007/978-3-030-60447-9_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60446-2

  • Online ISBN: 978-3-030-60447-9

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