Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/85724
Registo completo
Campo DC | Valor | Idioma |
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dc.contributor.author | Rodrigues, Nelson Ricardo Pereira | por |
dc.contributor.author | Costa, Nuno Miguel Cerqueira | por |
dc.contributor.author | Melo, César Gonçalo Macedo | por |
dc.contributor.author | Abbasi, Ali | por |
dc.contributor.author | Fonseca, Jaime C. | por |
dc.contributor.author | Cardoso, Paulo | por |
dc.contributor.author | Borges, João | por |
dc.date.accessioned | 2023-07-26T11:09:28Z | - |
dc.date.available | 2023-07-26T11:09:28Z | - |
dc.date.issued | 2023-06-15 | - |
dc.identifier.citation | Rodrigues, N.R.P.; da Costa, N.M.C.; Melo, C.; Abbasi, A.; Fonseca, J.C.; Cardoso, P.; Borges, J. Fusion Object Detection and Action Recognition to Predict Violent Action. Sensors 2023, 23, 5610. https://doi.org/10.3390/s23125610 | por |
dc.identifier.issn | 1424-8220 | por |
dc.identifier.uri | https://hdl.handle.net/1822/85724 | - |
dc.description.abstract | In the context of Shared Autonomous Vehicles, the need to monitor the environment inside the car will be crucial. This article focuses on the application of deep learning algorithms to present a fusion monitoring solution which was three different algorithms: a violent action detection system, which recognizes violent behaviors between passengers, a violent object detection system, and a lost items detection system. Public datasets were used for object detection algorithms (COCO and TAO) to train state-of-the-art algorithms such as YOLOv5. For violent action detection, the MoLa InCar dataset was used to train on state-of-the-art algorithms such as I3D, R(2+1)D, SlowFast, TSN, and TSM. Finally, an embedded automotive solution was used to demonstrate that both methods are running in real-time. | por |
dc.description.sponsorship | Work has been supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. This work was partly financed by European social funds through the Portugal 2020 program, and via national funds through FCT—Foundation for Science and Technology, within the scope of projects POCH-02-5369-FSE-000006. The author would also like to acknowledge FCT for the attributed Doctoral grant PD/BDE/150500/2019. | por |
dc.language.iso | eng | por |
dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00319%2F2020/PT | por |
dc.relation | POCH-02-5369-FSE-000006 | por |
dc.relation | info:eu-repo/grantAgreement/FCT/POR_NORTE/PD%2FBDE%2F150500%2F2019/PT | por |
dc.rights | openAccess | por |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | por |
dc.subject | Machine learning | por |
dc.subject | Visual intelligence | por |
dc.subject | Object detection | por |
dc.subject | Image processing | por |
dc.subject | Action recognition | por |
dc.subject | Autonomous vehicles | por |
dc.title | Fusion object detection and action recognition to predict violent action | por |
dc.type | article | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://www.mdpi.com/1424-8220/23/12/5610 | por |
oaire.citationStartPage | 1 | por |
oaire.citationEndPage | 21 | por |
oaire.citationIssue | 12 | por |
oaire.citationVolume | 23 | por |
dc.date.updated | 2023-06-27T13:23:26Z | - |
dc.identifier.eissn | 1424-8220 | - |
dc.identifier.doi | 10.3390/s23125610 | por |
dc.identifier.pmid | 37420776 | por |
sdum.journal | Sensors | por |
oaire.version | VoR | por |
dc.identifier.articlenumber | 5610 | por |
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sensors-23-05610.pdf | 3,55 MB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons