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Designing a High-Performance Deep Learning Theoretical Model for Biomedical Image Segmentation by Using Key Elements of the Latest U-Net-Based Architectures

Title: Designing a High-Performance Deep Learning Theoretical Model for Biomedical Image Segmentation by Using Key Elements of the Latest U-Net-Based Architectures
Authors: Luca, Andreea Roxana; Ursuleanu, Tudor Florin; Gheorghe, Liliana; Grigorovici, Roxana; Iancu, Stefan; Hlusneac, Maria; Preda, Cristina; Grigorovici, Alexandru
Source: Journal of Computer and Communications ; volume 09, issue 07, page 8-20 ; ISSN 2327-5219 2327-5227
Publisher Information: Scientific Research Publishing, Inc.
Publication Year: 2021
Document Type: article in journal/newspaper
Language: unknown
DOI: 10.4236/jcc.2021.97002
Availability: https://doi.org/10.4236/jcc.2021.97002; https://www.scirp.org/journal/paperinformation?paperid=110763; https://www.scirp.org/xml/110763.xml
Rights: http://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.EC3087D6
Database: BASE