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dc.contributor.authorPalomo-Ferrer, Esteban José 
dc.contributor.authorZafra-Santisteban, Miguel A.
dc.contributor.authorLuque-Baena, Rafael Marcos 
dc.date.accessioned2022-11-10T11:21:20Z
dc.date.available2022-11-10T11:21:20Z
dc.date.created2022
dc.date.issued2022
dc.identifier.urihttps://hdl.handle.net/10630/25393
dc.description.abstractPneumonia is an infectious and deadly disease which strikes over millions of people. Usually, chest X-rays are used by radiotherapist to diagnose pneumonia. In this paper, a Computer- Aided Diagnosis (CAD) system for pneumonia detection in chest X-ray images is proposed. This system is based on Convolutional Neural Networks (CNNs) which are able to classify the image into two classes (pneumonia or normal). Experimental results show that the proposed system obtained an accuracy rate of 98.59%.es_ES
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.es_ES
dc.language.isoenges_ES
dc.subjectInteligencia artificiales_ES
dc.subjectRedes neuronales (Informática)es_ES
dc.subjectTórax - Radiografíaes_ES
dc.subjectNeumoníaes_ES
dc.subject.otherpneumonia detectiones_ES
dc.subject.otherchest X-ray imageses_ES
dc.subject.otherconvolutional neural networkses_ES
dc.subject.othercomputer-aided diagnosises_ES
dc.titlePneumonia Detection in Chest X-ray Images using Convolutional Neural Networkses_ES
dc.typeconference outputes_ES
dc.centroE.T.S.I. Informáticaes_ES
dc.relation.eventtitle2022 IEEE INTERNATIONAL CONFERENCE ON METROLOGY FOR EXTENDED REALITY, ARTIFICIAL INTELLIGENCE AND NEURAL ENGINEERINGes_ES
dc.relation.eventplaceRoma, Italiaes_ES
dc.relation.eventdate26/10/2022es_ES
dc.departamentoLenguajes y Ciencias de la Computación
dc.rights.accessRightsopen accesses_ES


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