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Diagnosis of Malaria Using Double Hidden Layer Extreme Learning Machine Algorithm With CNN Feature Extraction and Parasite Inflator

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dc.contributor.authorGoni, Md. Omaer Faruq
dc.contributor.authorMondal, Md. Nazrul Islam
dc.contributor.authorIslam, Riazul
dc.contributor.authorNahiduzzaman, Md.
dc.contributor.authorIslam, Md. Robiul
dc.contributor.authorAnower, Md. Shamim
dc.contributor.authorKwak, Kyung Sup
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.date.accessioned2024-01-09T11:41:00Z
dc.date.available2024-01-09T11:41:00Z
dc.date.issued2023-01-05
dc.description10.13039/501100003725-National Research Foundation of Korea-Grant Korean Government (Ministry of Science and ICT) (Grant Number: NRF-2020R1A2B5B02002478)en
dc.description.statusPeer revieweden
dc.format.extent14
dc.format.extent4770605
dc.identifier282591824
dc.identifier800b7587-bd35-44c8-b12e-fc7d5e7168df
dc.identifier85147200404
dc.identifier.citationGoni, M O F, Mondal, M N I, Islam, R, Nahiduzzaman, M, Islam, M R, Anower, M S & Kwak, K S 2023, 'Diagnosis of Malaria Using Double Hidden Layer Extreme Learning Machine Algorithm With CNN Feature Extraction and Parasite Inflator', IEEE Access, vol. 11, pp. 4117-4130. https://doi.org/10.1109/ACCESS.2023.3234279en
dc.identifier.doi10.1109/ACCESS.2023.3234279
dc.identifier.issn2169-3536
dc.identifier.otherORCID: /0000-0003-2968-9561/work/150764375
dc.identifier.urihttps://hdl.handle.net/2164/22512
dc.identifier.vol11en
dc.language.isoeng
dc.relation.ispartofIEEE Accessen
dc.subjectSDG 3 - Good Health and Well-beingen
dc.subjectRB Pathologyen
dc.subjectQA76 Computer softwareen
dc.subject.lccRBen
dc.subject.lccQA76en
dc.titleDiagnosis of Malaria Using Double Hidden Layer Extreme Learning Machine Algorithm With CNN Feature Extraction and Parasite Inflatoren
dc.typeJournal articleen

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