Czech Sign Language Single Hand Alphabet Letters Classification

0536892 - ÚT 2021 RIV US eng C - Conference Paper (international conference)
Krejsa, Jiří - Věchet, Stanislav
Czech Sign Language Single Hand Alphabet Letters Classification.
Proceedings of the 2020 19th International Conference on Mechatronics - Mechatronika, ME 2020. New York: Institute of Electrical and Electronics Engineers Inc., 2020 - (Maga, D.; Hajek, J.), s. 1-341. ISBN 978-172815601-9.
[International Conference on Mechatronics - Mechatronika /19./. Praha (CZ), 02.12.2020-04.12.2020]
Institutional support: RVO:61388998
Keywords : Czech sign language * convolution neural network * classification
OECD category: Automation and control systems
https://ieeexplore.ieee.org/document/9286667

The paper deals with the classification of images of Czech sign language alphabet, single handed version in particular, without diacritics. The classification is performed by convolution neural network using TensorFlow computational library. Network topology, data acquisition and automatic labelling and obtained results are described in the paper. The accuracy on the test data - captured images of a person not previously seen by the network – was over 87%.
Permanent Link: http://hdl.handle.net/11104/0316609