Modification of U-Net neural network in the task of multichannel satellite images segmentation

Results of training of convolutional neural network for satellite four-channel image segmentation are performed. Input images contain blue, green, red and near-infrared channels. The algorithm was trained to detect buildings and other urban areas. Modification of the U-Net neural network with two encoders was used. The values of Sorensen coefficient and Jaccard index were calculated for 16 different urban regions. © 2019 IEEE.