Detail publikace
Czech Sign Language Single Hand Alphabet Classification with MediaPipe
ŠNAJDER, J. BEDNAŘÍK, J.
Anglický název
Czech Sign Language Single Hand Alphabet Classification with MediaPipe
Typ
článek ve sborníku mimo WoS a Scopus
Jazyk
en
Originální abstrakt
The paper presents the classification of static images of the single-handed Czech sign language alphabet. It uses the framework MediaPipe for annotation, and the classification is performed by a neural network using the TensorFlow computational library. The flow of the proposed method, data acquisition, preprocessing, and training are described in the paper. Obtained results consist of the classification success rate of the validation dataset for various MediaPipe configurations. The overall success rate was around 94%.
Anglický abstrakt
The paper presents the classification of static images of the single-handed Czech sign language alphabet. It uses the framework MediaPipe for annotation, and the classification is performed by a neural network using the TensorFlow computational library. The flow of the proposed method, data acquisition, preprocessing, and training are described in the paper. Obtained results consist of the classification success rate of the validation dataset for various MediaPipe configurations. The overall success rate was around 94%.
Klíčová slova anglicky
Czech sign language, Fingerspelling, Classification, Mediapipe, Neural network
Vydáno
09.05.2022
Nakladatel
Institute of Theoretical and Applied Mechanics of the Czech Academy of Sciences
Místo
Prague
ISBN
ISBN 978-80-86246-51
ISSN
1805-8256
Kniha
ENGINEERING MECHANICS 2022
Číslo edice
1
Strany od–do
381–384
Počet stran
4
BIBTEX
@inproceedings{BUT178377,
author="Jan {Šnajder} and Josef {Bednařík},
title="Czech Sign Language Single Hand Alphabet Classification with MediaPipe",
booktitle="ENGINEERING MECHANICS 2022",
year="2022",
month="May",
pages="381--384",
publisher="Institute of Theoretical and Applied Mechanics of the Czech Academy of Sciences",
address="Prague",
isbn="ISBN 978-80-86246-51",
issn="1805-8256"
}