Please use this identifier to cite or link to this item:
https://hdl.handle.net/10316/100609
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Malta, Ana | - |
dc.contributor.author | Mendes, Mateus | - |
dc.contributor.author | Farinha, Torres | - |
dc.date.accessioned | 2022-07-07T08:11:40Z | - |
dc.date.available | 2022-07-07T08:11:40Z | - |
dc.date.issued | 2021 | - |
dc.identifier.issn | 2076-3417 | pt |
dc.identifier.uri | https://hdl.handle.net/10316/100609 | - |
dc.description.abstract | Maintenance professionals and other technical staff regularly need to learn to identify new parts in car engines and other equipment. The present work proposes a model of a task assistant based on a deep learning neural network. A YOLOv5 network is used for recognizing some of the constituent parts of an automobile. A dataset of car engine images was created and eight car parts were marked in the images. Then, the neural network was trained to detect each part. The results show that YOLOv5s is able to successfully detect the parts in real time video streams, with high accuracy, thus being useful as an aid to train professionals learning to deal with new equipment using augmented reality. The architecture of an object recognition system using augmented reality glasses is also designed. | pt |
dc.language.iso | eng | pt |
dc.relation | UIDB/00048/2020 | pt |
dc.rights | openAccess | pt |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt |
dc.subject | Augmented reality | pt |
dc.subject | Car engine dataset | pt |
dc.subject | Car part detection | pt |
dc.subject | Task assistant | pt |
dc.subject | YOLOv5 | pt |
dc.title | Augmented Reality Maintenance Assistant Using YOLOv5 | pt |
dc.type | article | - |
degois.publication.firstPage | 4758 | pt |
degois.publication.issue | 11 | pt |
degois.publication.title | Applied Sciences (Switzerland) | pt |
dc.peerreviewed | yes | pt |
dc.identifier.doi | 10.3390/app11114758 | pt |
degois.publication.volume | 11 | pt |
dc.date.embargo | 2021-01-01 | * |
uc.date.periodoEmbargo | 0 | pt |
item.fulltext | Com Texto completo | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.languageiso639-1 | en | - |
item.openairetype | article | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | open | - |
crisitem.project.grantno | INSTITUTE OF SYSTEMS AND ROBOTICS - ISR - COIMBRA | - |
crisitem.author.researchunit | ISR - Institute of Systems and Robotics | - |
crisitem.author.researchunit | CEMMPRE - Centre for Mechanical Engineering, Materials and Processes | - |
crisitem.author.parentresearchunit | University of Coimbra | - |
crisitem.author.orcid | 0000-0003-4313-7966 | - |
crisitem.author.orcid | 0000-0002-9694-8079 | - |
Appears in Collections: | I&D ISR - Artigos em Revistas Internacionais I&D CEMMPRE - Artigos em Revistas Internacionais |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Augmented-reality-maintenance-assistant-using-yolov5Applied-Sciences-Switzerland.pdf | 1.47 MB | Adobe PDF | View/Open |
SCOPUSTM
Citations
82
checked on Jun 24, 2024
WEB OF SCIENCETM
Citations
39
checked on Jun 2, 2024
Page view(s)
145
checked on Oct 16, 2024
Download(s)
140
checked on Oct 16, 2024
Google ScholarTM
Check
Altmetric
Altmetric
This item is licensed under a Creative Commons License