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dc.creatorGeorgakopoulos S.V., Kottari K., Delibasis K., Plagianakos V.P., Maglogiannis I.en
dc.date.accessioned2023-01-31T07:40:19Z
dc.date.available2023-01-31T07:40:19Z
dc.date.issued2017
dc.identifier10.1007/978-3-319-65172-9_34
dc.identifier.isbn9783319651712
dc.identifier.issn18650929
dc.identifier.urihttp://hdl.handle.net/11615/72062
dc.description.abstractIn this work, we report the use of convolutional neural networks for the detection of malignant melanomas against nevus skin lesions in a dataset of dermoscopic images of the same magnification. The technique of transfer learning is utilized to compensate for the limited size of the available image dataset. Results show that including transfer learning in training CNN architectures improves significantly the achieved classification results. © Springer International Publishing AG 2017.en
dc.language.isoenen
dc.sourceCommunications in Computer and Information Scienceen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85028313699&doi=10.1007%2f978-3-319-65172-9_34&partnerID=40&md5=a2672b31cd81b98081ddd0059dd7f631
dc.subjectConvolutionen
dc.subjectDermatologyen
dc.subjectNeural networksen
dc.subjectConvolutional neural networken
dc.subjectDiagnostic systemsen
dc.subjectMelanoma detectionen
dc.subjectSkin lesionen
dc.subjectTransfer learningen
dc.subjectNetwork architectureen
dc.subjectSpringer Verlagen
dc.titleDetection of malignant melanomas in dermoscopic images using convolutional neural network with transfer learningen
dc.typeconferenceItemen


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