Original title: Defect Detection In Fibered Material Using Methods Of Machine Learning
Authors: Lang, Matěj
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: SILON s.r.o is manufacturer of polyester fibres which get used in wide range of applications, many of them requiring highest quality material. Due to manufacturing processes, some fibres are not drawn properly and stay in the fiber as bundles, or brittle, thick threads. Proposed lab station should automate process of quality check of each batch. It consists of linescan camera scanner and computer with software for detection and analysis of defects.
Keywords: CNN; convolutional neural network; defect detection; EEICT; FCN; fluorescence; fully convolutional network; linescan camera; polyester fiber; quality check; Rhodamine B; scanner
Host item entry: Proceedings of the 25st Conference STUDENT EEICT 2019, ISBN 978-80-214-5735-5

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/186685

Permalink: http://www.nusl.cz/ntk/nusl-414587


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Conference materials > Papers