A Retinal Verssel Detection Approach Using Convolution Neural Network

dc.contributor.author	Sengur, Abdulkadir
dc.contributor.author	Guo, Yanhui
dc.contributor.author	Budak, Umit
dc.contributor.author	Vespa, Lucas J.
dc.date.accessioned	2021-12-16T09:07:31Z
dc.date.available	2021-12-16T09:07:31Z
dc.date.issued	2017
dc.identifier.isbn	978-1-5386-1880-6
dc.identifier.uri	http://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/10406
dc.description.abstract	Computer-aided detection (CAD) provides an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is an important step to identify the retinal disease regions automatically and accurately. However, RV de
dc.language.iso	English
dc.publisher	Ieee
dc.relation.ispartof	2017 International Artificial Intelligence and Data Processing Symposium (IDAP)
dc.source	2017 Internatıonal Artıfıcıal Intellıgence And Data Processıng Symposıum (Idap)
dc.title	A Retinal Verssel Detection Approach Using Convolution Neural Network
dc.type	Proceedings Paper
dc.identifier.wos	WOS:000426868700171

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