Comparison of Deep Learning Models AlexNet and GoogLeNet in Detection of Pneumonia and Covid19

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dc.authoridTaşkın, Deniz/0000-0001-7374-8165
dc.authoridOzsoy, Yaren/0000-0002-0811-5748
dc.authorwosidÖzsoy, Yaren/HSH-3342-2023
dc.authorwosidTaşkın, Deniz/KIC-9302-2024
dc.contributor.authorOzsoy, Yaren
dc.contributor.authorTaskin, Deniz
dc.date.accessioned2024-06-12T10:59:11Z
dc.date.available2024-06-12T10:59:11Z
dc.date.issued2021
dc.departmentTrakya Üniversitesien_US
dc.description7th International Conference on Engineering and Emerging Technologies (ICEET) -- OCT 27-28, 2021 -- Istanbul, TURKEYen_US
dc.description.abstractDue to the rapidly increasing population, workload is increasing in the field of health as well as in many different fields. In the increasing workload, there are models and algorithms developed to reduce the burden of our doctors by providing insight into the diagnosis of pneumonia. Early diagnosis of many diseases, especially pneumonia, is important in reducing the death rate. Therefore, diagnosing the disease with deep learning methods is an important development in medicine. In this study, AlexNet and GoogLeNet models were run and their performances were evaluated. Looking at the results, it turns out that the deep learning model is successful in diagnosing the presence of the disease. Open access data sets were used due to limited data in medicine. The data set consists of a total of 6357 chest x-rays. Accuracy, true positive rate, false positive rate and precision rates were determined by creating confusion matrix in the study.en_US
dc.description.sponsorshipSuper Univ,Altinbas Univ,IEEE Turkey Sect,IEEEen_US
dc.identifier.doi10.1109/ICEET53442.2021.9659627
dc.identifier.endpage163en_US
dc.identifier.isbn978-1-6654-2714-2
dc.identifier.scopus2-s2.0-85124645532en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage161en_US
dc.identifier.urihttps://doi.org/10.1109/ICEET53442.2021.9659627
dc.identifier.urihttps://hdl.handle.net/20.500.14551/20353
dc.identifier.wosWOS:000828108100029en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2021 7th International Conference On Engineering And Emerging Technologies (Iceet 2021)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDeep Learningen_US
dc.subjectAlexneten_US
dc.subjectGoogleneten_US
dc.subjectESAen_US
dc.titleComparison of Deep Learning Models AlexNet and GoogLeNet in Detection of Pneumonia and Covid19en_US
dc.typeConference Objecten_US

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