Optical Detection of UAVs Using Deep Convolutional Neural Networks

Drone technologies advance has become the new weapon of choice for terror and criminal applications for civilian and military targets. Hence, it has opened for researchers a new challenging task as the safety and security of privacy, public and state entities. In the current manuscript, we propose a novel drone detection approach using deep Convolutional Neural Networks CNNs aims to provide a computer aided method defined as Visual Geometry Group 16 VGG 16 Model for Unmanned Aerial Vehicle UAVs identification and recognition using image processing that can effectively classify the drone and non-drone scenes, from the captured RGB based images. Features extraction is then applied using machine learning classifiers to enhance the accuracy of the detection systems. The drone's detection algorithm with deep CNNs has demonstrated the best performance for object detection with accuracy of 94.57%. Nevertheless, the experimental results show high reliability of the designed model to be validated and used for drone detection and recognition.