Abstract
Proposed an improved approach to the segmentation of multispectral images using Convolutional Neural Networks (CNN). The original algorithm was described earlier. It took into account some errors that could arise during the processing of SNA images using a sliding window. The proposed modification uses the and indices, which have a high correlation coefficient with real objects present in the images, also images pyramids were used.
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