Synthesis of neural network structure for the analysis of complex structured ocular fundus images

This paper proposes an algorithm for synthesizing a neural network (NN) structure to analyze complex structured, low entropy, ocular fundus images, characterized by iterative tuning of the adaptive model's solver modules. This algorithm will assist in synthesizing models of NNs that meet the pr...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Tatarkanov Aslan, Alexandrov Islam, Glashev Rasul
Formato:	article
Lenguaje:	EN
Publicado:	Institut za istrazivanja i projektovanja u privredi 2021
Materias:	artificial neural networks synthesis algorithm complex structured images diagnosis of ocular fundus pathologies automation of non-invasive diagnostics Technology T Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/3306733cf374425bbaf9aff124d49e7b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:3306733cf374425bbaf9aff124d49e7b
record_format	dspace
spelling	oai:doaj.org-article:3306733cf374425bbaf9aff124d49e7b2021-12-05T21:23:07ZSynthesis of neural network structure for the analysis of complex structured ocular fundus images1451-41171821-319710.5937/jaes0-31238https://doaj.org/article/3306733cf374425bbaf9aff124d49e7b2021-01-01T00:00:00Zhttps://scindeks-clanci.ceon.rs/data/pdf/1451-4117/2021/1451-41172102344T.pdfhttps://doaj.org/toc/1451-4117https://doaj.org/toc/1821-3197This paper proposes an algorithm for synthesizing a neural network (NN) structure to analyze complex structured, low entropy, ocular fundus images, characterized by iterative tuning of the adaptive model's solver modules. This algorithm will assist in synthesizing models of NNs that meet the predetermined characteristics of the classification quality. The relevance of automating the process of ocular diagnostics of fundus pathologies is due to the need to develop domestic medical decision-making systems. Because of using the developed algorithm, the NN structure is synthesized, which will include two solver modules, and is intended to classify the dual-alternative information. Automated hybrid NN structures for intelligent segmentation of complex structured, low entropy, retinal images should provide increased efficiency of ocular diagnostics of fundus pathologies, reduce the burden on specialists, and decrease the negative impact of the human factor in diagnosis.Tatarkanov AslanAlexandrov IslamGlashev RasulInstitut za istrazivanja i projektovanja u privrediarticleartificial neural networkssynthesis algorithmcomplex structured imagesdiagnosis of ocular fundus pathologiesautomation of non-invasive diagnosticsTechnologyTEngineering (General). Civil engineering (General)TA1-2040ENIstrazivanja i projektovanja za privredu, Vol 19, Iss 2, Pp 344-355 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	artificial neural networks synthesis algorithm complex structured images diagnosis of ocular fundus pathologies automation of non-invasive diagnostics Technology T Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	artificial neural networks synthesis algorithm complex structured images diagnosis of ocular fundus pathologies automation of non-invasive diagnostics Technology T Engineering (General). Civil engineering (General) TA1-2040 Tatarkanov Aslan Alexandrov Islam Glashev Rasul Synthesis of neural network structure for the analysis of complex structured ocular fundus images
description	This paper proposes an algorithm for synthesizing a neural network (NN) structure to analyze complex structured, low entropy, ocular fundus images, characterized by iterative tuning of the adaptive model's solver modules. This algorithm will assist in synthesizing models of NNs that meet the predetermined characteristics of the classification quality. The relevance of automating the process of ocular diagnostics of fundus pathologies is due to the need to develop domestic medical decision-making systems. Because of using the developed algorithm, the NN structure is synthesized, which will include two solver modules, and is intended to classify the dual-alternative information. Automated hybrid NN structures for intelligent segmentation of complex structured, low entropy, retinal images should provide increased efficiency of ocular diagnostics of fundus pathologies, reduce the burden on specialists, and decrease the negative impact of the human factor in diagnosis.
format	article
author	Tatarkanov Aslan Alexandrov Islam Glashev Rasul
author_facet	Tatarkanov Aslan Alexandrov Islam Glashev Rasul
author_sort	Tatarkanov Aslan
title	Synthesis of neural network structure for the analysis of complex structured ocular fundus images
title_short	Synthesis of neural network structure for the analysis of complex structured ocular fundus images
title_full	Synthesis of neural network structure for the analysis of complex structured ocular fundus images
title_fullStr	Synthesis of neural network structure for the analysis of complex structured ocular fundus images
title_full_unstemmed	Synthesis of neural network structure for the analysis of complex structured ocular fundus images
title_sort	synthesis of neural network structure for the analysis of complex structured ocular fundus images
publisher	Institut za istrazivanja i projektovanja u privredi
publishDate	2021
url	https://doaj.org/article/3306733cf374425bbaf9aff124d49e7b
work_keys_str_mv	AT tatarkanovaslan synthesisofneuralnetworkstructurefortheanalysisofcomplexstructuredocularfundusimages AT alexandrovislam synthesisofneuralnetworkstructurefortheanalysisofcomplexstructuredocularfundusimages AT glashevrasul synthesisofneuralnetworkstructurefortheanalysisofcomplexstructuredocularfundusimages
_version_	1718370993900093440

Synthesis of neural network structure for the analysis of complex structured ocular fundus images

Ejemplares similares