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dc.contributor.authorMartsenyuk, Vasyl-
dc.contributor.authorMilian, Nazar-
dc.contributor.authorMilian, Roksolana-
dc.date.accessioned2022-01-19T10:17:39Z-
dc.date.available2022-01-19T10:17:39Z-
dc.date.issued2021-06-22-
dc.identifier.citationMartsenyuk V., Milian N., Milian R. The U-Net model application for retinal vessels segmentation using the machine learning library TensorFlow // Information and Digital Technologies : The International Conference on (22-24 June 2021 Zilina, Slovakia). Zilina. 2021.uk_UA
dc.identifier.isbn978-1-6654-3692-2-
dc.identifier.issn2575-677X-
dc.identifier.urihttp://dspace.tnpu.edu.ua/handle/123456789/24117-
dc.description.abstractIn this article the implementation of neural network architecture based on a dense U-Net network is proposed. It is noted that retinal blood vessels are the basis for clinical diagnosis of some diseases. A review of the convolutional networks use for classification tasks and generalizion retinal vessel segmentation algorithms is performed. The general process of the neural network is presented. The differences between the real and the obtained results were evaluated. Evaluation of the neural network is carried out on several parameters. The figure with the recognized blood vessels as a result of the model is presented.uk_UA
dc.language.isoenuk_UA
dc.subjectmachine learninguk_UA
dc.subjectneural networkuk_UA
dc.subjectmachine learning libraryuk_UA
dc.subjectretinal vessels segmentationuk_UA
dc.titleThe U-Net model application for retinal vessels segmentation using the machine learning library TensorFlowuk_UA
dc.typeConference Abstractuk_UA
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