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Deep Learning Based Skin Cancer Diagnosis

dc.contributor.authorArik, Alper
dc.contributor.authorGolcuk, Mesut
dc.contributor.authorKarsligil, Elif Mine
dc.date.accessioned2026-06-27T14:05:34Z
dc.date.issued2017
dc.description.abstractMelanoma is the deadliest form of skin cancer. Early diagnosis has vital importance in the healing of the disease. As human expertise is in limited, automated systems capable of identifying disease could save lives, reduce unnecessary intervention and costs. Toward this goal, in this paper we propose a system that uses recent deep learning methods that are capable of classitication of skin lesions for melanoma detection.en
dc.identifier.isbn978-1-5090-6494-6
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/20.500.14981/56895
dc.identifier.wos000413813100315
dc.language.isotur
dc.publisherIEEE
dc.relation.conference25th Signal Processing and Communications Applications Conference (SIU)
dc.relation.ispartof2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
dc.subjectDeep learning
dc.subjectmachine learning
dc.subjectskin cancer diagnosis
dc.subjectmelanoma detection
dc.subjectconvolutional neural networks
dc.subjectAcoustics
dc.subjectComputer Science
dc.subjectEngineering
dc.subjectTelecommunications
dc.titleDeep Learning Based Skin Cancer Diagnosis
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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