Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/163182
Full metadata record
DC FieldValueLanguage
dc.creatorBernardo Maria Avides Moreira Amorim Alves
dc.date.accessioned2025-11-11T19:38:03Z-
dc.date.available2025-11-11T19:38:03Z-
dc.date.issued2024-10-10
dc.date.submitted2024-11-19
dc.identifier.othersigarra:697172
dc.identifier.urihttps://hdl.handle.net/10216/163182-
dc.language.isoeng
dc.rightsopenAccess
dc.subjectEngenharia electrotécnica, electrónica e informática
dc.subjectElectrical engineering, Electronic engineering, Information engineering
dc.titleAdvancing Transport Quantification: Unlocking Insights through Deep Learning Models
dc.typeDissertação
dc.contributor.uportoFaculdade de Engenharia
dc.identifier.doi10.34626/x5xt-vr13
dc.identifier.tid203856317
dc.subject.fosCiências da engenharia e tecnologias::Engenharia electrotécnica, electrónica e informática
dc.subject.fosEngineering and technology::Electrical engineering, Electronic engineering, Information engineering
thesis.degree.disciplineMestrado em Engenharia Eletrotécnica e de Computadores
thesis.degree.grantorFaculdade de Engenharia
thesis.degree.grantorUniversidade do Porto
thesis.degree.level1
Appears in Collections:FEUP - Dissertação

Files in This Item:
File Description SizeFormat 
697172.pdfAdvancing Transport Quantification: Unlocking Insights through Deep Learning Models1.92 MBAdobe PDFThumbnail
View/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.