Prihanto, Surya and Effendy, Nazrul and Nopriadi, Nopriadi (2024) Hand gesture-based automatic door security system using squeeze and excitation residual networks. IAES International Journal of Artificial Intelligence, 13 (2). 1619 – 1624. ISSN 20894872
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Abstract
Viruses can be transmitted due to various aspects; one spreads through airborne droplets or the touch of multiple objects. This can occur in any area, including the entrance to the house or access to a room or deposit box. The spread of viruses that cause diseases like Covid-19 has caused many human casualties, and there is still the possibility of similar conditions appearing in the future. Several things need to be done to reduce the chances of spreading disease due to viruses, including developing contactless security support methods. This paper proposes a security system using hand gesture recognition using squeeze and excitation residual networks (SE-ResNet). This research offers a hand gesture recognition system for an automatic door system using SE-ResNet and the residual network (ResNet). © 2024, Institute of Advanced Engineering and Science. All rights reserved.
Item Type: | Article |
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Additional Information: | Cited by: 1; All Open Access, Hybrid Gold Open Access |
Uncontrolled Keywords: | Convolutional neural network; Hand gesture recognition; Residual network; Security; Squeeze excitation network |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Faculty of Engineering > Nuclear and Physics Engineering Department |
Depositing User: | Rita Yulianti Yulianti |
Date Deposited: | 16 Apr 2025 01:34 |
Last Modified: | 16 Apr 2025 01:34 |
URI: | https://ir.lib.ugm.ac.id/id/eprint/13139 |