Cardiotocography Analysis based on Segmentation-based Fractal Texture Decomposition and Extreme Learning Machine

dc.contributor.author	Comert, Zafer
dc.contributor.author	Kocamaz, Adnan Fatih
dc.date.accessioned	2021-12-16T09:07:33Z
dc.date.available	2021-12-16T09:07:33Z
dc.date.issued	2017
dc.identifier.isbn	978-1-5090-6494-6
dc.identifier.issn	2165-0608
dc.identifier.uri	http://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/10417
dc.description.abstract	Fetal heart rate (FHR) has notable patterns for the assessment of fetal physiology and typical stress conditions. FHR signals are obtained using cardiotocography (CTG) devices also providing uterine activities simultaneously and fetal movements. In this s
dc.language.iso	Turkish
dc.publisher	Ieee
dc.relation.ispartof	25th Signal Processing and Communications Applications Conference (SIU)
dc.source	2017 25Th Sıgnal Processıng And Communıcatıons Applıcatıons Conference (Sıu)
dc.title	Cardiotocography Analysis based on Segmentation-based Fractal Texture Decomposition and Extreme Learning Machine
dc.type	Proceedings Paper
dc.identifier.wos	WOS:000413813100260

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