Skip navigation
Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/45796
Title: Neural Network Approach for Estimating the Level and Volume of Liquid in Transparent Containers
Authors: Golovko, V.
Mikhno, E.
Mamyha, A.
Keywords: материалы конференций;conference proceedings;training dataset;deep neural network;container volume;liquid level;liquid volume
Issue Date: 2021
Publisher: UIIP NASB
Citation: Golovko, V. Neural Network Approach for Estimating the Level and Volume of Liquid in Transparent Containers / Golovko V., Mikhno E., Mamyha A. // Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021) : Proceedings of the 15th International Conference, 21–24 Sept. 2021, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2021. – P. 56–60.
Abstract: The main purpose of this paper is to represent and investigate a neural network approach for determining the volume of the container and the volume of an opaque liquid in a transparent bounded container. To achieve the purpose, we apply two models of neural networks, namely AlexNet and eXnet. We have prepared and created a training dataset. The results of experiments on determining the level and volume of liquid in transparent bounded containers are presented.
URI: https://libeldoc.bsuir.by/handle/123456789/45796
Appears in Collections:Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021)

Files in This Item:
File Description SizeFormat 
Golovko_Neural.pdf1.73 MBAdobe PDFView/Open
Show full item record Google Scholar

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.