Application of Convolutional Gated Recurrent Units U-Net for Distinguishing between Retinitis Pigmentosa and Cone–Rod Dystrophy Cover

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Application of Convolutional Gated Recurrent Units U-Net for Distinguishing between Retinitis Pigmentosa and Cone–Rod Dystrophy

Acta Mechanica et Automatica

Volume 18 (2024): Issue 3 (September 2024)

By: Maria Skublewska-Paszkowska , Pawel Powroznik , Robert Rejdak and Katarzyna Nowomiejska

Open Access

|Jul 2024

Authors

Maria Skublewska-Paszkowska

maria.paszkowska@pollub.pl

Faculty of Electrical Engineering and Computer Science, Department of Computer Science, Lublin University of Technology, Lublin, Poland

Pawel Powroznik

p.powroznik@pollub.pl

Faculty of Electrical Engineering and Computer Science, Department of Computer Science, Lublin University of Technology, Lublin, Poland

Robert Rejdak

robertrejdak@yahoo.com

Faculty of Medicine, Chair and Department of General and Pediatric Ophthalmology, Medical University of Lublin, Lublin, Poland

Katarzyna Nowomiejska

katarzyna.nowomiejska@umlub.pl

Faculty of Medicine, Chair and Department of General and Pediatric Ophthalmology, Medical University of Lublin, Lublin, Poland

DOI: https://doi.org/10.2478/ama-2024-0054 | Journal eISSN: 2300-5319 | Journal ISSN: 1898-4088

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Language: English

Page range: 505 - 513

Submitted on: Jul 22, 2023

Accepted on: Jan 29, 2024

Published on: Jul 25, 2024

Published by: Bialystok University of Technology

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

retinitis pigmentosa,

convolutional GRU U-Net,

classification,

Related subjects:

Civil engineering,

Environmental engineering,

Electrical engineering,

Mechanical engineering,

Bioengineering and biomedical engineering,

© 2024 Maria Skublewska-Paszkowska, Pawel Powroznik, Robert Rejdak, Katarzyna Nowomiejska, published by Bialystok University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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