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Vol.11, No.1, February 2022. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
The Performance of Thai Sign Language Recognition with 2D Convolutional Neural Network Based on NVIDIA Jetson Nano Developer Kit
Eakbodin Gedkhaw
© 2022 Eakbodin Gedkhaw, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 11, Issue 1, Pages 411-419, ISSN 2217-8309, DOI: 10.18421/TEM111-52, February 2022.
Received: 24 November 2021. Revised: 13 February 2022.
Abstract:
Thai Sign Language Recognition is a Thai Sign Language learning computer recognition. The system constructs an architecture of T-SLR by TSR- 2DCNN based on NVIDIA Jetson Nano Developer Kit. It is a novelty of automatic translation TSL innovation and reveals the performance of feature extraction and classification to reduce crashed system, overloaded or automatic reboot while complicated processing occurs. The dataset contains 7 gestures in TSL, training images are 7,000 images and validation images are 700 images. The result compares with many techniques as shown that TSR-2DCNN can increase the performance of TSLR in real-time, effectiveness with an accuracy of 0.9914 and loss of 0.03537.
Keywords –Thai Sign Language, Convolutional Neural Network, NVDIA Jetson Nano, Gesture Image Segmentation, Classification. |
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