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International Journal of Intelligent Systems and Applications(IJISA)

ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online)

Published By: MECS Press

IJISA Vol.12, No.6, Dec. 2020

Deep Learning Sign Language Recognition System Based on Wi-Fi CSI

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Author(s)

Marwa R. M. Bastwesy, Nada M. ElShennawy, Mohamed T. Faheem Saidahmed

Index Terms

Wireless;Device-free sensing;Channel State Information;Sign Language Recognition;Deep Learning;WiFi Imaging

Abstract

Many sensing gesture recognition systems based on Wi-Fi signals are introduced because of the commercial off-the-shelf Wi-Fi devices without any need for additional equipment. In this paper, a deep learning-based sign language recognition system is proposed. Wi-Fi CSI amplitude and phase information is used as input to the proposed model. The proposed model uses three types of deep learning: CNN, LSTM, and ABLSTM with a complete study of the impact of optimizers, the use of amplitude and phase of CSI, and preprocessing phase. Accuracy, F-score, Precision, and recall are used as performance metrics to evaluate the proposed model. The proposed model achieves 99.855%, 99.674%, 99.734%, and 93.84% average recognition accuracy for the lab, home, lab + home, and 5 different users in a lab environment, respectively. Experimental results show that the proposed model can effectively detect sign gestures in complex environments compared with some deep learning recognition models. 

Cite This Paper

Muhammad Junaid Arshad, Muhammad Umair, Saima Munawar, Nasir Naveed, Humaira Naeem, "Improving Cloud Data Encryption Using Customized Genetic Algorithm", International Journal of Intelligent Systems and Applications(IJISA), Vol.12, No.6, pp.33-45, 2020. DOI: 10.5815/ijisa.2020.06.03

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