Please use this identifier to cite or link to this item: http://dspace.tnpu.edu.ua/handle/123456789/24117
Title: The U-Net model application for retinal vessels segmentation using the machine learning library TensorFlow
Authors: Martsenyuk, Vasyl
Milian, Nazar
Milian, Roksolana
Bibliographic description (Ukraine): Martsenyuk 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.
Issue Date: 22-Jun-2021
Keywords: machine learning
neural network
machine learning library
retinal vessels segmentation
Abstract: In 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.
URI: http://dspace.tnpu.edu.ua/handle/123456789/24117
ISBN: 978-1-6654-3692-2
ISSN: 2575-677X
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