Deep-learning based pipeline for high voltage tower detection
| dc.audience.degree | MÀSTER UNIVERSITARI EN APLICACIONS I TECNOLOGIES PER ALS SISTEMES AERIS NO TRIPULATS (DRONS) (Pla 2017) |
| dc.audience.educationlevel | Màster |
| dc.audience.mediator | Escola d'Enginyeria de Telecomunicació i Aeroespacial de Castelldefels |
| dc.contributor | Meseguer Pallarès, Roc |
| dc.contributor.author | Mañé Verdú, Laia |
| dc.contributor.covenantee | Venturi Unmanned Technologies |
| dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors |
| dc.date.accessioned | 2021-09-21T11:43:19Z |
| dc.date.issued | 2021-09-15 |
| dc.date.updated | 2021-09-18T03:31:16Z |
| dc.identifier.slug | PRISMA-161667 |
| dc.identifier.uri | https://hdl.handle.net/2117/351829 |
| dc.language.iso | eng |
| dc.publisher | Universitat Politècnica de Catalunya |
| dc.rights.access | Restricted access - confidentiality agreement |
| dc.subject | Àrees temàtiques de la UPC::Aeronàutica i espai::Aeronaus |
| dc.subject.lcsh | Drone aircraft--Equipment and supplies |
| dc.subject.lemac | Avions no tripulats -- Equip electrònic |
| dc.subject.other | Drone |
| dc.subject.other | UAV |
| dc.subject.other | RPAS |
| dc.subject.other | UAS |
| dc.subject.other | Tensorflow |
| dc.subject.other | Detection |
| dc.subject.other | IA |
| dc.subject.other | Machine learning |
| dc.subject.other | Darknet |
| dc.subject.other | YOLO |
| dc.title | Deep-learning based pipeline for high voltage tower detection |
| dc.type | Master thesis |
| dspace.entity.type | Publication |
| local.emails | laia.mane.v@gmail.com |
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