Rodyti trumpą aprašą

dc.contributor.authorCicėnas, Benediktas
dc.contributor.authorAbromavičius, Vytautas
dc.date.accessioned2023-09-18T16:19:34Z
dc.date.available2023-09-18T16:19:34Z
dc.date.issued2022
dc.identifier.other(SCOPUS_ID)85132194074
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/113207
dc.description.abstractWith the advance of Covid-19 pneumonia and its complications increased the load of radiologists several times. The pneumonia detection usually is performed by examination of chest X-Ray radiograph by the radiologists. This process is tedious, influenced by fatigue and may lead to mistakes. Computer-Aided diagnostic systems shows the potential for improving accuracy. In this work, we present investigation for pneumonia detection based on several convolutional neural network architectures via transfer learning. Additionally, we propose a method for preparing data from the Radiological Society of North America Pneumonia Detection Challenge to achieve better results.eng
dc.formatPDF
dc.format.extentp. 1-4
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyConference Proceedings Citation Index - Science (Web of Science)
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyIEEE Xplore
dc.rightsLaisvai prieinamas internete
dc.source.urihttps://ieeexplore.ieee.org/document/9781683
dc.source.urihttps://talpykla.elaba.lt/elaba-fedora/objects/elaba:135820667/datastreams/MAIN/content
dc.titleInvestigation of pneumonia detection using convolutional neural networks
dc.typeStraipsnis konferencijos darbų leidinyje Web of Science DB / Paper in conference publication in Web of Science DB
dcterms.references15
dc.type.pubtypeP1a - Straipsnis konferencijos darbų leidinyje Web of Science DB / Article in conference proceedings Web of Science DB
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyElektronikos fakultetas / Faculty of Electronics
dc.subject.researchfieldT 001 - Elektros ir elektronikos inžinerija / Electrical and electronic engineering
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.studydirectionB04 - Informatikos inžinerija / Informatics engineering
dc.subject.studydirectionE09 - Elektronikos inžinerija / Electronic engineering
dc.subject.vgtuprioritizedfieldsIK0303 - Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems
dc.subject.ltspecializationsL106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies
dc.subject.enconvolutional neural networks
dc.subject.endiseases
dc.subject.enmachine learning
dc.subject.enpneumonia
dc.subject.enX-Rays
dcterms.sourcetitle2022 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), 21 April 2022, Vilnius, Lithuania / organized by: Vilnius Gediminas Technical University
dc.publisher.nameIEEE
dc.publisher.cityPiscataway, NJ
dc.identifier.doi2-s2.0-85132194074
dc.identifier.doi85132194074
dc.identifier.doi0
dc.identifier.doi137608473
dc.identifier.doi000848697000004
dc.identifier.doi10.1109/eStream56157.2022.9781683
dc.identifier.elaba135820667


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