Mostrar el registro sencillo del ítem

dc.contributor.authorMolina-Cabello, Miguel Ángel 
dc.contributor.authorThurnhofer Hemsi, Karl
dc.contributor.authorMaza Quiroga, Rosa María
dc.contributor.authorDomínguez, Enrique
dc.contributor.authorLópez-Rubio, Ezequiel 
dc.contributor.authorMolina-Cabello, Miguel Ángel 
dc.date.accessioned2021-07-30T08:27:28Z
dc.date.available2021-07-30T08:27:28Z
dc.date.created2021
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/10630/22717
dc.description.abstractSkin cancer is one of the most prevalent diseases among people. Physicians have a challenge every time they have to determine whether a diseased skin is benign or malign. There exist clinical diagnosis methods (such as the ABCDE rule), but they depend mainly on the physician’s experience and might be imprecise. Deep learning models are very extended in medical image analysis, and several deep models have been proposed for moles classification. In this work, a convolutional neural network is proposed to support the diagnosis procedure. The proposed MobileNetV2-based model is improved by a shifting technique, providing better performance than raw transfer learning models for moles classification. Experiments show that this technique could be applied to the state-of-the-art deep models to improve their results and outperform the training phase.es_ES
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.es_ES
dc.language.isoenges_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectCiencias de la computaciónes_ES
dc.subjectLenguaje de computaciónes_ES
dc.subjectProgramaciónes_ES
dc.subjectCancer de pieles_ES
dc.subjectDiagnóstico médicoes_ES
dc.subject.otherImage processinges_ES
dc.subject.otherDeep learninges_ES
dc.subject.otherClassificationes_ES
dc.subject.otherSkin lesiones_ES
dc.titleEnhanced transfer learning model by image shifting on a square lattice for skin lesion malignancy assessmentes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.centroE.T.S.I. Informáticaes_ES
dc.relation.eventtitleInternational Joint Conference on Neural Networks 2021 (IJCNN 2021)es_ES
dc.relation.eventplaceVirtuales_ES
dc.relation.eventdateJulio de 2021es_ES


Ficheros en el ítem

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem