With the developing technology, technological blessings make human life easier and help them every day. Unmanned aerial vehicles (UAV), which is one of the technological blessings, have shown themselves in many fields, especially in fields such as the military, defense industry, photography, and hobby. With the development of defense systems with UAVs, the security of railways has also been left to UAVs. In this study, while the foreign matter separation is made on the railway by using the deep learning model in real-time, the image taken on the UAV is simultaneously controlled by using the image processing method. The fact that the deep learning model has a 0.99 mAP rate increases the reliability of the model.
Today, bombing activities are frequently on the agenda. Bomb devices placed under vehicles are the most common example of bombing activities. Shopping malls, military camps, etc. In places, vehicles are allowed to pass by checking under the vehicle with a mirror. This situation may leave the door open to mistakes that can be made by the personnel checking under the vehicle. In this study, an automatic controlled system was designed for vehicle passage. It is aimed to take under-vehicle images of the vehicles to be taken to a military campus, depending on the license plate recognition system, and to allow these images to pass into the military campus in a controlled manner after determining whether there is a foreign object under the vehicle by using artificial intelligence methods. An interface screen has been created for the designed system. If the incoming license plate is registered in the system and there is no foreign object under the vehicle, the barrier is opened and the vehicle passes.
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