Vol.11, No.1, February 2022.                                                                                                                                                                           ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



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.
Accepted: 18 February 2022.
Published: 28 February 2022.




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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