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- W3113764772 abstract "A system that secures an area from trespassing drones that might bring threat is in demand these days since drones became easily-available to the public and it became easier to operate. This paper proposes an anti-drone system that uses visual sensing to detect drones. A Faster R-CNN (Region-based Convolutional Neural Network) with ResNet-101 (Residual Neural Network-101) networks are used in this paper using a dataset from the SafeShore project. The network's accuracy is 93.40% and it has successfully detected drones in the simulation that has been done." @default.
- W3113764772 created "2021-01-05" @default.
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- W3113764772 date "2020-10-21" @default.
- W3113764772 modified "2023-10-17" @default.
- W3113764772 title "Anti-Drone System: A Visual-based Drone Detection using Neural Networks" @default.
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- W3113764772 doi "https://doi.org/10.1109/ictc49870.2020.9289397" @default.
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