Detection of Drone Using Deep Learning Techniques

The detection of flying unmanned aerial vehicles (UAVs) or drones within a specific airspace. This technology has become increasingly important in recent years due to the growing popularity and safety use of drones for military purposes. In image processing, it is essential to detect and track air targets, especially UAVs. In the field of diagnosis and classification of objects, there are always many problems that prevent the development of rapid and significant progress in this area. The advanced classification methods such as convolutional neural
networks and support vector machines have been developed. The drone was detected using three methods of classification of convolutional neural network (CNN), support vector
machine (SVM), and nearest neighbor. The outcomes show that CNN,SVM, and nearest neighbor have total accuracy of 95%, 88%,and 80%, respectively. Compared with other classifiers with the same experimental conditions, the accuracy of the convolutional neural network classifier is satisfactory.