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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/42395
Title: Neuro-Symbolic Artificial Intelligence: Application for Control the Quality of Product Labeling
Authors: Golovko, V. A.
Kroshchanka, A. A.
Kovalev, M. V.
Taberko, V. V.
Ivaniuk, D.
Головко, В. А.
Крощенко, А. А.
Ковалев, М. В.
Таберко, В. В.
Keywords: публикации ученых
deep neural networks
object detection
Issue Date: 2020
Publisher: Springer, Германия
Citation: Neuro-Symbolic Artificial Intelligence: Application for Control the Quality of Product Labeling / V. Golovko[et. al.] // Open Semantic Technologies for Intelligent System : 10th International Conference OSTIS 2020, Minsk, 19–22 February 2020 / Belarusian State University of Informatics and Radioelectronics ; eds.: V.Golenkov [et. al.]. – Minsk, 2020. – P. 81–101. – DOI: https://doi.org/10.1007/978-3-030-60447-9_6.
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.
URI: https://libeldoc.bsuir.by/handle/123456789/42395
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