Age Estimation from Retinal Images: Different Image Preprocessing Approaches

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but.event.date25.04.2023cs
but.event.titleSTUDENT EEICT 2023cs
dc.contributor.authorKadlec, Vojtěch
dc.date.accessioned2023-07-17T05:57:36Z
dc.date.available2023-07-17T05:57:36Z
dc.date.issued2023cs
dc.description.abstractHuman age is considered an important biometricparameter that is often difficult to determine. Previous studieshave shown that the non-specific general anatomical and physiologicalcharacteristics seen on fundus images are all likely signs ofageing. This paper focuses on age estimation from retinal imageswith different image preprocessing approaches together withproposed image detail enhancement method. Convolution neuralnetwork framework is based on the ResNet-34 architecturetogether with the Consistent Rank Logits algorithm estimatingage as an ordinal variable. The best model achieved a meanabsolute error of 3.47 years, outperforming existing modelsestimating age from retinal images.en
dc.formattextcs
dc.format.extent37-40cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings II of the 29st Conference STUDENT EEICT 2023: Selected papers. s. 37-40. ISBN 978-80-214-6154-3cs
dc.identifier.doi10.13164/eeict.2023.37
dc.identifier.isbn978-80-214-6154-3
dc.identifier.issn2788-1334
dc.identifier.urihttp://hdl.handle.net/11012/210707
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings II of the 29st Conference STUDENT EEICT 2023: Selected papersen
dc.relation.urihttps://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_2_v2.pdfcs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectDeep learningen
dc.subjectage estimationen
dc.subjectretinal images,retinal image preprocessingen
dc.titleAge Estimation from Retinal Images: Different Image Preprocessing Approachesen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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