SETTING, TRAINING AND TESTING OF A CONVOLUTIONAL NEURAL NETWORK TO COMLETE THE TASK OF THEMATIC PROCESSING OF SATELLITE IMAGES
We describe an algorithm based on a convolutional neural network that detects cloud and snow covers in satellite images. Algorithm accuracy was evaluated using machine learning metrics. The proposed algorithm is fully automatic.
Keywords: neural networks, training, testing, texture, remote sensing, Electro-L, multi-zone scanning instrument used for hydrometeorological support
