Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11779/1546
Full metadata record
DC FieldValueLanguage
dc.contributor.authorTemiz, Hüseyin-
dc.contributor.authorGökberk, Berk-
dc.contributor.authorAkarun, Lale-
dc.date.accessioned2021-08-24T10:43:13Z
dc.date.available2021-08-24T10:43:13Z
dc.date.issued2021-
dc.identifier.citationTemiz, H., Gökberk, B., & Akarun, L. (9-11 June 2021). TurCoins: Turkish Republic Coin Dataset. In 2021 29th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). https://doi.org/10.1109/SIU53274.2021.9477957en_US
dc.identifier.issn9781665436496-
dc.identifier.urihttps://hdl.handle.net/20.500.11779/1546-
dc.identifier.urihttps://doi.org/10.1109/SIU53274.2021.9477957-
dc.description.abstractIn this paper, we present a novel and comprehensive dataset which contains Turkish Republic coins minted since 1924 and present a deep learning based system that can automatically classify coins. The proposed dataset consists of 11080 coin images from 138 different classes. To classify coins, we utilize a pre-trained neural network (ResNet50) which is pre-trained on ImageNet. We train the pre-trained neural networks on our dataset by transfer learning. The imbalanced nature of the dataset causes the classifier to show lower performance in classes with fewer samples. To alleviate the imbalance problem, we propose a StyleGAN2-based augmentation method providing realisticfake coins for rare classes. The dataset will be published in http://turcoins.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectResidual neural networksen_US
dc.subjectBarium , Neural networksen_US
dc.subjectArten_US
dc.subjectTransfer learningen_US
dc.subjectSupport vector machinesen_US
dc.subjectSignal processingen_US
dc.titleTurCoins: Turkish republic coin dataseten_US
dc.title.alternativeTurCoins: Türkiye cumhuriyeti madeni para veri kümesien_US
dc.typeConference Objecten_US
dc.identifier.doi10.1109/SIU53274.2021.9477957-
dc.identifier.scopus2-s2.0-85111419467en_US
dc.authoridBerk Gökberk / 0000-0001-6299-1610-
dc.description.woscitationindexConference Proceedings Citation Index - Science-
dc.description.WoSDocumentTypeProceedings Paper
dc.description.WoSInternationalCollaborationUluslararası işbirliği ile yapılmayan - HAYIRen_US
dc.description.WoSPublishedMonthHaziranen_US
dc.description.WoSIndexDate2022en_US
dc.description.WoSYOKperiodYÖK - 2021-22en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.startpage1-4en_US
dc.departmentMühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.relation.journalSIU 2021 - 29th IEEE Conference on Signal Processing and Communications Applications, Proceedingsen_US
dc.identifier.wosWOS:000808100700198en_US
dc.institutionauthorGökberk, Berk-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextembargo_20400101-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.openairetypeConference Object-
Appears in Collections:Bilgisayar Mühendisliği Bölümü koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Files in This Item:
File Description SizeFormat 
TurCoins_Turkish_Republic_Coin_Dataset.pdf
  Until 2040-01-01
Proceeding papers2.45 MBAdobe PDFView/Open    Request a copy
Show simple item record



CORE Recommender

Page view(s)

4
checked on Jun 26, 2024

Google ScholarTM

Check




Altmetric


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