Aircraft Detection from Satellite Images Using ATA-Plane Data Set

Satellite image analysis is a field of study in the field of image processing for many civil and military applications. Satellite images have many civilian applications, including recognition, detection and classification of regions, buildings, roads, aircrafts and other man-made objects. Among these, especially aircraft detection is strategically important for military applications and forms the basis of this study. In the first phase of the study, a new dataset composed of airplanes at different airports on Google Earth's satellite images is prepared to eliminate the lack of data set in this field. In the second stage, the detection of aircraft was carried out by using algorithms based on Convolutional Neural Network. Transfer Learning was used to improve the performance of this process. The accuracy rate obtained as a result of Transfer Learning with previously trained network Alexnet, was 91%.