Abstract: In image processing, it is essential to detect and track air targets,
especially UAVs. In this paper, we detect the flying drone using a fisheye
camera. 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. During the previous decades, a couple of advanced
classification methods such as convolutional neural networks and support vector
machines have been developed. In this study, 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.