ПРОПОЗИЦІЇ ЩОДО ПІДВИЩЕННЯ ТОЧНОСТІ СЕГМЕНТАЦІЇ МІСЬКИХ БУДОВ НА ЦИФРОВИХ КОСМІЧНИХ І АЕРОФОТОЗНІМКАХ ПРИ АВТОМАТИЗОВАНОМУ МОНІТОРИНГУ МІСЬКОГО СЕРЕДОВ

Abstract

In basis of topography that is used in a military sphere, - a capture lies the methods of study of locality. On it, receipt of quantitative and quality descriptions of locality on space and to the airphotos - is one of basic parts of military topography presently. Architecture of U-Net zdkztncz effective enough for the decision of different tasks, such as segmentation of neuron structures, sciagraphy et cetera. A network is characterized by a coder with the sequence of levels of convolutional and maximal pool. Thus, the layer of decoding contains the mirror sequence of convolutional that transponirovan’s. He behaves as traditional automatic encode. Extractor of functions of U-Net can be modernized for the improvement of maps of segmentation of municipal structures. Unclear to the neuron decorate a pattern Vanga-Мandelja it maybe to use the classifier of the modified decoder in quality U-Net . Formal presentation of neuron network ensemble of neuron networks is in-process offered on the basis of the modified rolled up neuron network for segmentation of municipal structures (automatic encode) of U-Net as super position of functions. Architecture of ensemble of neuron networks is worked out on the basis of the modified convolutional neuron network (СNN) for segmentation of municipal structures (automatic encode) of U-Net. Modification (automatic encode) of U-Net is conducted due to modification of subnet of withdrawal of signs with using as encoder preliminary trained deep СNN VGG, and similarly due to realization of classifier of automatic encode with the use of the modified unclear neuron network Vanga-Мandelja on the basis of INМТ2 for on a pixel classification of certain municipal structures and the generalized topology of by a neuron network model is worked out for segmentation of municipal structures. Modification (automatic encode) of U-Net will allow to promote exactness of segmentation of municipal structures on digital space and airphotos at the automated monitoring of municipal environment.