1. Repositório Aberto da Universidade do Porto
  2. FEUP - Faculdade de Engenharia
  3. FEUP - Dissertação
Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/166232
Full metadata record
DC FieldValueLanguage
dc.creatorTiago Daniel dos Santos Leitão e Sousa
dc.date.accessioned2026-01-26T04:29:45Z-
dc.date.available2026-01-26T04:29:45Z-
dc.date.issued2025-03-20
dc.date.submitted2025-04-09
dc.identifier.othersigarra:717925
dc.identifier.urihttps://hdl.handle.net/10216/166232-
dc.language.isoeng
dc.rightsembargoedAccess
dc.subjectEngenharia electrotécnica, electrónica e informática
dc.subjectElectrical engineering, Electronic engineering, Information engineering
dc.titleDeep learning strategies for UAV-based inspection of photovoltaic panels
dc.typeDissertação
dc.date.embargo2028-03-19
dc.contributor.uportoFaculdade de Engenharia
dc.identifier.doi10.34626/mpa0-a760
dc.identifier.tid204119855
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
rcaap.embargofctProjeto de investigação com dados da empresa.
Appears in Collections:FEUP - Dissertação

Files in This Item:
File Description SizeFormat 
717925.pdf
  Restricted Access		Deep learning strategies for UAV-based inspection of photovoltaic panels23.01 MBAdobe PDFView/Open
Show simple item record Recommend this item Display Statistics


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