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Classification of Czech sign language alphabet letters using cnn – preliminary study
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SYSNO ASEP 0535189 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Classification of Czech sign language alphabet letters using cnn – preliminary study Author(s) Krejsa, Jiří (UT-L) RID, ORCID
Věchet, Stanislav (UT-L) RID, ORCIDNumber of authors 2 Source Title ENGINEERING MECHANICS 2020. - Brno : Brno University of Technology Institute of Solid Mechanics, Mechatronics and Biomechanics, 2020 / Fuis V. - ISSN 1805-8248 - ISBN 978-80-214-5896-3 Pages s. 310-313 Number of pages 4 s. Publication form Print - P Action International Conference Engineering Mechanics 2020 /26./ Event date 24.11.2020 - 25.11.2020 VEvent location Brno Country CZ - Czech Republic Event type WRD Language eng - English Country CZ - Czech Republic Keywords classification ; sign language ; convolution neural network Subject RIV IN - Informatics, Computer Science OECD category Robotics and automatic control Institutional support UT-L - RVO:61388998 UT WOS 000667956100070 DOI 10.21495/5896-3-310 Annotation Abstract: The paper deals with the classification of Czech sign language single hand alphabet letters from static images using convolutional neural network (CNN). Proposed CNN architecture exhibits about 71% successful rate of classifying the letters signed by the person not included in the training data set. Workplace Institute of Thermomechanics Contact Marie Kajprová, kajprova@it.cas.cz, Tel.: 266 053 154 ; Jana Lahovská, jaja@it.cas.cz, Tel.: 266 053 823 Year of Publishing 2021
Number of the records: 1