Optimization Of Convolutional Neural Network For Object Recognition On Satellite Images

Investigation about using convolutional neural networks for detection geo-objects on the satellite images from Landsat-8 was presented. U-NET convolutional neural network architecture for implementing the recognition algorithm was used. The neural network was trained by the marked image base “Urban Atlas”. Urban Atlas contains images of 21 classes, but in current research was used 3 classes: “Forest”, “Agriculture” and “Water”. Images obtained from the Landsat-8 satellites are used for estimation of automatic object detection quality. To analyze the accuracy of the object detection algorithm, the selected regions were compared with the areas by previously marked by experts. Two modification of object detector were proposed and analyzing.