Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/46288
Full metadata record
DC FieldValueLanguage
dc.contributor.authorVANHERLE, Bram-
dc.contributor.authorMOONEN, Steven-
dc.contributor.authorVAN REETH, Frank-
dc.contributor.authorMICHIELS, Nick-
dc.date.accessioned2025-06-23T14:30:26Z-
dc.date.available2025-06-23T14:30:26Z-
dc.date.issued2022-
dc.date.submitted2025-05-26T10:44:31Z-
dc.identifier.urihttp://hdl.handle.net/1942/46288-
dc.description.abstractObject detection for the DIMO dataset. Uses the Mask-RCNN model. This is the official implementation of Analysis of Training Object Detection Models with Synthetic Data, published in BMVC: British Machine Vision Conference, 2022. Source code for the following scientific publication: Vanherle, B., Moonen, S., Van Reeth, F., and Michiels, N. (2022). Analysis of Training Object Detection Models with Synthetic Data. 33rd British Machine Vision Conference 2022, BMVC 2022, London, UK, November 21-24, 2022. Retrieved from https://bmvc2022.mpi-inf.mpg.de/0833.pdf-
dc.description.sponsorshipPILS SBO: Product Inspection with Little Supervision. Flanders Make (Belgium). awardNumber:null. 02ndjfz59-
dc.description.sponsorshipBOF Special Research Fund. Hasselt University. awardNumber:null. 10.13039/501100009550-
dc.language.isoen-
dc.publisherZenodo-
dc.titleEDM-Research/DIMO_ObjectDetection: v1.0-
dc.typeOther-
local.bibliographicCitation.jcatO-
local.type.refereedNon-Refereed-
local.type.specifiedSoftware Package-
dc.identifier.doi10.5281/zenodo.15517548-
dc.identifier.urlhttps://zenodo.org/doi/10.5281/zenodo.15517548-
local.provider.typedatacite-
local.uhasselt.internationalno-
local.contributor.datacreatorVanherle, Bram-
local.contributor.datacreatorMoonen, Steven-
local.contributor.datacreatorVan Reeth, Frank-
local.contributor.datacreatorMichiels, Nick-
local.contributororcid.datacreator0000-0002-7047-5867-
dc.rights.accessCreative Commons Attribution 4.0 International-
item.contributorVANHERLE, Bram-
item.contributorMOONEN, Steven-
item.contributorVAN REETH, Frank-
item.contributorMICHIELS, Nick-
item.contributorVanherle, Bram-
item.contributorMoonen, Steven-
item.contributorVan Reeth, Frank-
item.contributorMichiels, Nick-
item.fulltextNo Fulltext-
item.accessRightsClosed Access-
item.fullcitationVANHERLE, Bram; MOONEN, Steven; VAN REETH, Frank & MICHIELS, NickVanherle, Bram; Moonen, Steven; Van Reeth, Frank & Michiels, Nick (2022) EDM-Research/DIMO_ObjectDetection: v1.0.-
Appears in Collections:Research publications
Show simple item record

Google ScholarTM

Check

Altmetric


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