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Hand gesture-based automatic door security system using squeeze and excitation residual networks

Prihanto, SuryaEffendy, NazrulNopriadi, Nopriadi
IAES International Journal of Artificial Intelligence (IJ-AI) (Sinta 1)Vol. 0 No. 01 Juni 2024
DOI10.11591/ijai.v13.i2.pp1619-1624

Abstrak

Viruses can be transmitted in various ways; 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).

Kata Kunci

Convolutional neural networkHand gesture recognitionResidual networkSecuritySqueeze excitation network

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Hand gesture-based automatic door security system using squeeze and excitation residual networks | IAES International Journal of Artificial Intelligence (IJ-AI) | Publiora