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Detail publikačního výsledku
ŠNAJDER, J.; KREJSA, J.
Originální název
Classification of Czech Sign Language Alphabet Diacritics via LSTM
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
The paper presents the classification of image sequences of the single-handed Czech sign language alphabet diacritics. Since diacritics are expressed by the motion of the hand, the classification is performed by the Long Short-Term Memory recurrent neural network. Annotation of the dataset is done by the MediaPipe framework, and the neural network is constructed with the TensorFlow computational library. The paper describes the proposed method's flow, data acquisition, preprocessing, and training. Obtained results consist of the validation dataset's classification success rate and testing on whole signed words and sentences. The overall success rate was around 88%.
Anglický abstrakt
Klíčová slova
Czech sign language; classification; MediaPipe; image sequence; Long Short-Term Memory
Klíčová slova v angličtině
Autoři
Rok RIV
2023
Vydáno
09.12.2022
Nakladatel
Institute of Electrical and Electronics Engineers Inc.
Místo
Pilsen
ISBN
978-1-6654-1039-7
Kniha
2022 20th International Conference on Mechatronics - Mechatronika (ME)
Edice
1st
Strany od
178
Strany do
182
Strany počet
5
URL
https://ieeexplore.ieee.org/document/9983436/
Plný text v Digitální knihovně
http://hdl.handle.net/
BibTex
@inproceedings{BUT182996, author="Jan {Šnajder} and Jiří {Krejsa}", title="Classification of Czech Sign Language Alphabet Diacritics via LSTM", booktitle="2022 20th International Conference on Mechatronics - Mechatronika (ME)", year="2022", series="1st", pages="178--182", publisher="Institute of Electrical and Electronics Engineers Inc.", address="Pilsen", doi="10.1109/ME54704.2022.9983436", isbn="978-1-6654-1039-7", url="https://ieeexplore.ieee.org/document/9983436/" }